The main trends of the BI market in Russia

Main article: Trends in the IT market in Russia

2023-2024

The rapid development of Russian BI platforms, provoked by the departure of Western players from the domestic market, brings its results. The number of solutions is growing, the range of possibilities of the most common and mature systems continues to expand. According to experts, in most cases, on the basis of a particular Russian BI platform, 90% or more business requests in BI can be closed.

Increased security

The process of migration to Russian BI platforms, as well as the evolution of analytical areas in government agencies, corporations with state participation, as well as simply in large commercial holdings, implies increased security and the emergence of new access control tasks. And although many users seek to delay the transition from the foreign BI platforms that have become familiar, it will not be possible to delay this process indefinitely.

There are companies that manage to renew annual subscriptions in different ways. It is clear that this is not forever. The software becomes obsolete, the impossibility of prompt update increases both the risks of failures from various kinds of incompatibilities and the risks of information security. Using the software without vendor support, trainings, updates is far from as convenient as having all this. Therefore, my forecast is that in two or three years all or almost all will leave this software. Moreover, there are worthy alternatives in the register of Russian software and in friendly China, - emphasizes Julius Goldberg, head of BI at GlowByte.

Meanwhile, Russian developers see requests for increased security and continue to introduce new functions into their products, help customers implement integrations with enterprise information systems. Leading players also continue to certify their products according to FSTEC requirements in order to provide the opportunity to work with BI enterprises from among CII and other organizations with high information security requirements.

Many trends in 2022 continued to dominate in 2023. This includes data security and privacy: strengthening security measures and attention to compliance with access restrictions on complex role models, FSTEC certification, working with a Russian secure and certified technology stack, such as the Astra Linux operating system or the GosTech platform, "says Vladimir Bakhov, partner of the Digital Economy League.

In 2024, the demand for security of solutions and data will remain an actual trend. Competition in the market among domestic solutions will be at the same level, which will lead to an improvement in the quality and functionality of products. In general, the Russian BI market will continue to develop and adapt to the changing requirements of users and legislation, - said Maxim Komlev, CTO of Quillis.

Self-Service и low(no) code

One of the main claims of potential customers to Russian BI platforms in 2022 was a shortage of independent work opportunities for analysts and business users. Since then, the level of support for Self-Service technologies has increased significantly. Most vendors have somehow implemented the ability to design simple dashboards and configure visualizations in low-code or no-code mode.

Meanwhile, not every Russian platform allows you to get a deeper Self-Service. For example, when it comes to working independently with data models, the range of potentially suitable solutions is sharply narrowed. And when it is necessary to provide analysts with the ability to work with unique queries without additional programming and knowledge of SQL, the choice is actually narrowed to 2-3 systems with the most developed functionality. According to experts, you can choose the right one only after a detailed analysis of the real capabilities of the platform in relation to end-user requests.

Artificial Intelligence in BI

It is impossible not to mention artificial intelligence, the introduction of which into analytical tools is not only a Russian, but also a global trend. And among the Russian platforms there are several interesting examples of AI work.

Many companies - both Russian and foreign - seek to add capabilities for Natural Language Processing (NLP) user request and automatic construction of analytical panels using artificial intelligence, - said Anastasia Ostapenko, head of the BI competence center at Axenix (ex-Accenture).

Various schemes for using AI can already be found in Russian BI platforms. For example, some vendors solve optimization problems for various narrow analytics problems by creating new AI models for their products.

We continue to develop in the field of AI and are actively integrating neural network tools (deep learning) into Visary BI. In November of this year, we successfully defended the Visary BI modernization project, within the framework of which we showed all the possibilities for sharing two technologies (implemented with the support of RFRIT). The no-code Visary AI module with a built-in training data generation service allows you to independently create, train, test and export models for solving computer vision (CV) problems. The information obtained thanks to AI is combined into predefined Visary BI dashboards. At the same time, special technical skills are not needed to implement the entire process, all work is carried out in intuitive interfaces, - says Roman Dzvinko, executive director of the SPC "BusinessAutomatics," about his platform.

Another example is the use of AI for a wide range of tasks and speeding up analysts. A similar scheme is implemented in the ViTalkGPT chatbot, which helps Visiology users formulate DAX requests, taking into account the features of operator support in Visiology 3, to prepare Python scripts for the Vixtract ETL module. According to company representatives, this approach saves up to 20% of analyst time, as well as formulate requests for DAX, even if the user has only a minimal idea of ​ ​ this language.

The platform Delta BI has an Explain the Difference module - this is a kind of built-in analyzer. You can select two parallel periods for analysis and ask the system to explain what factors influenced the difference in results, - cites another example of the use of AI in, BI Maria Averina a partner in managing the department of business intelligence. Navicon

Excel Support

Many vendors are actively working to expand their solutions and add new features to them. However, this is often due not only to the introduction of the most modern tools, but also to the support of technologies familiar to users. Given that in Russia, many users continue to work in ordinary spreadsheets, there is a demand for connecting such sources to the analytical circuit. So, as an example, we can cite the Tabulate module from Delta BI, which is actually built-in Excel. It is designed to solve the problems of scenario modeling: you can open ready-made Excel reports right in the system, combine them with data from the analytical model, conduct scenario modeling and display results on dashboards.

Another scheme for solving this issue is demonstrated by the Visiology ecosystem, in which a special Smart Forms module has been developing for more than 5 years. Right in the browser, users can fill out interactive web forms and send information directly to the BI platform store, and the ViLoader mechanism allows you to load entire Excel tables.

Integrated approach

Another stumbling block that prevented a faster transition to Russian BI platforms is the rather narrow specialization of most Russian analytical tools. If Microsoft , for example, Oracle they could offer a wide infrastructure of integrated and tested solutions, Russian BI is only now forming such connections.

We try to form a corporate governance platform in which BI is just one of the modules. It is important that you can "out of the box," without programming, solve most of the problems of the financial and production blocks. Already, the tasks of financial planning, budgeting, management reporting, maintenance and repair monitoring, risk management, etc. are simply being solved. We were able to give customers a very powerful tool combining the functionality of process management, analysis, visualization, forecasting and planning, replacing leading Western solutions, "emphasizes Artem Grishkovsky, Commercial Director of Trusted Environment.

An interesting approach is demonstrated by some companies that have recently brought their BI solutions to the market. They can offer them along with other software products they sold previously. For example, PIX Robotics chose this strategy. According to representatives of the vendor, the PIX RPA robotic system, which has been on the market for about 5 years, is now supplied with a relatively new PIX BI, the development of which began only in the spring of 2022. Thanks to this, all users of the robotization system can work with the new solution.

We are developing the direction of automation of strategic planning and budgeting processes, where the functionality of data visualization is an integral part. We are ready to offer not just a BI platform, but business solutions of the EPM (Enterprise Performance Management) class. The new Polymatica EPM product line is a set of tools that allow you to set business goals, track them, manage them and thus improve the efficiency of the company. Polymatica EPM, as part of our business platform, currently includes four standalone solutions: Integrated Planning (EPM-IP), Planning and Budgeting (EPM-BP), Sales and Operations Planning (EPM-SO), Cost Allocation (EPM-CA). The combination of these business solutions allows us, as a vendor, to provide all possible scenarios for planning and modeling the company's activities in maximum detail. Using them, our customers increase the efficiency of strategic, medium-term and operational planning processes for profitability management, - explains the development of the Polymatica platform Grigory Vorotyntsev.

Also on the market there were interesting solutions for connecting data from. 1C For example, in 2023, the company "Denwick" proposed a number of connectors that can be used to upload information from 1C to the most popular BI platforms. It is worth noting that this was, in principle, inaccessible to Western platforms, and such a practice serves as another argument for the introduction of Russian BI-solutions, since the established integrations allow analyzing data from 1C, which today becomes the main alternative to the departed Russia ERP systems.

Our main task as a vendor is the development of our flagship product "Forsyth. Analytical Platform. " In 2023, we launched a new, 10th version of the platform, which works in the web interface. But so that users can get used to new web tools, we leave the ability to use the desktop version. At the same time, users can work in parallel in both the thick client and the web - the versions are completely synchronized. In 2024, we plan to move all platform tools to the web application to the maximum. Developing the capabilities of the platform, we are primarily focused on the needs of large corporate customers, so we focus on improving performance, including when integrating with Russian software. As for our easy analytics tool, FlyBI, the product has seriously advanced over the year, increased functionality. We have a number of customers from different industries. Now FlyBI is used not only by state customers, from large federal structures to regional informatization centers, industrial enterprises, but also by small companies. The main vector of FlyBI development is the expansion of user capabilities and, for corporate customers, closer integration with the Forsyth digital analytical platform, - comments Yulia Kudryavtseva, Director of Strategic Development of Forsyth.

Data Storage - ClickHouse Course

A separate trend in 2023 was the increased focus on analytical data storage methods and enterprise data warehouse (DWH) building. Because high-performance storage, such as optimization, Oracle Exadata has become unavailable to customers even with large budgets. data storage

This year, we noted the growing need for customers to build and implement enterprise data warehousing. Every year, companies are increasing the volume of corporate data, business has a need to build a single storage that easily integrates with sources, quickly processes large amounts of data, while not loading other information systems of the company, - emphasizes Andrey Harlak, CTO of Qlev Solutions.

According to established best practices, vendors seek to reconstruct storage and translate it to DBMS open source. So, according to company representatives, most "FTO" often for storage facilities not related to, Big Data QCD is used on the basis. And PostgreSQL when it comes to big data or its frequent update, the choice falls on the column DBMS. ClickHouse

Quality data helps us make the right decisions. To get such data, you need to not only collect it, but also monitor the relevance and maintain its quality. This implies constant monitoring and management of the entire data process, - emphasizes the trend Maxim Komlev, CTO of Quillis.

The Delta BI system also has a built-in connector with ClickHouse. It allows you to seamlessly access the analytical DBMS and analyze the company's performance in real time. However, as practice shows, for effective analytics, it is not enough to simply install the ClickHouse DBMS - you need to organize a full-fledged corporate storage on its basis, which can become a long and expensive project.

The use of ClickHouse is becoming the standard in modern analytics, which is dictated by high performance requirements and is associated with the need to analyze really big data with reasonable consumption of hardware. However, in practice, in order for such a configuration to work quickly and reliably, there is a need for each project to do a lot of work on optimizing the data scheme in the data warehouse, and taking into account the many technical nuances of ClickHouse. This adds weeks and months to the launch date of the project, plus there are not many specialists in the labor market who can implement such a project, and they are very expensive. Therefore, when developing Visiology 3, we decided to embed managed ClickHouse directly into the platform so that users can simply download and work with data - without unnecessary time and financial costs. Numerous mechanisms for automatic caching and indexing have been created, special schemes for placing, copying and loading data have been developed, which today allow you to get the highest performance when analyzing billions of rows of data, even without the participation of a data storage specialist, - comments Nikita Ilyin, architect of Visiology.

2022-2023: Course on Self-service and effective import substitution

The Russian market for business analytics systems underwent a major transformation in 2022. The players who occupied the dominant market share left it, and the remaining vendors got the opportunity to show themselves. In a review of the Russian BI market, TAdviser talks about current trends in business analysis, and representatives of vendors share their innovations.

Import Substitution Rate

Although import substitution began several years ago, in reality, 2022 was the starting point for the start of a mass of projects to replace Western BI systems with Russian ones. At the same time, many companies have started adapting their solutions so that they can meet the expectations of users who are accustomed to a certain style of working with BI.

In fact, the transition from foreign BI to Russian for the company means a full-fledged implementation project, with all the ensuing consequences. You can't just take and transfer existing developments, for example, from Power BI, to domestic software. Customers need to take into account many points: the requirements of BI systems for data sources (not all Russian BI systems are democratic to the databases with which they work), the requirement for server equipment, the method of deployment (cloud or on-prem), the complexity of BI systems themselves and what requirements they have for the competencies of customer expertise centers, - comments Shchapov Roman, Commercial Director of Goodt.

Self-Service in a broad sense

Self-service is one of BI's most current trends overall. In recent years, foreign tools have taught us that many tasks can be solved in drag'n "drop mode, that a data model can be built in graphical mode, and for these tasks it is not necessary to have programming skills.

The strategic development of our BI platform is aimed at improving the convenience of the user interface and continuing the development of Self Service functionality. This is what the next release of Luxms BI 9.0 in January 2023 will be devoted to. One of the main innovations of the ninth version is the appearance of the Analyst's Personal Account, a convenient user mechanism in which you can configure and work inside an isolated sandbox. The analyst will be able to receive data, conduct research and have convenient functionality for further publication of dashboards within the organization or for presentation to management. Also in version 9.0 it is planned to seriously expand the functionality of the PivotTable. It will be possible to group and ungroup all content in the summary table, which will simplify the work with data for the work of analysts, for further decision-making, - notes Alexey Mednikov, Director of Innovations at Luxms Group of Companies.

At the same time, Russian platforms, according to the vendors themselves, have not yet reached the level of self-service, which world leaders can boast of, but are actively working in this direction and with each release reduce the requirements for user training, and also expand

One of the key development trends is still self-service solutions. The simplification and interactivity of the interface, its visualization contribute to connecting the maximum number of employees to the system for more efficient work and the formation of a global ecosystem, systematization and analytics of data from any source in different formats. Another trend that does not slow down is the introduction of artificial intelligence. In particular, Augmented Business Intelligence (ABI) can be noted. This is a new stage of development, because it combines not only familiar analytics, but also automated help of the system in building correct and informative visualization. In my opinion, this is a good benchmark for the development of the BI system of the future. Diamond BI places significant emphasis on the possibilities of conducting self-service analytics. Much attention is paid to the development of UX/UI. This gives even unprepared users convenient tools for self-analysis of data depending on their functional needs: from simple filtering and grouping to modifying the structure of reports and building semantic models, - emphasizes Vladimir Bakhov, partner of the Digital Economy League.

All Russian vendors pay special attention to self-service today, but solving this problem at the level of world leaders will take some time. According to Gartner analysts, one of the integral components of self-service is the integration of BI solutions into the business software ecosystem. And this is what experts are used to seeing in BI systems from Qlik, Tableau, Power BI - and even more so in Oracle or SAP products.

However, Russian solutions are also actively developing in the direction of integration. So, in road maps for the development of a number of products, the task is to embed BI content in third-party portals while maintaining interactivity, managing parameters and supporting SSO. And some large BI projects (for example, the analytical platform of the SME Corporation, implemented by the integrator Notamedia) already demonstrate the possibility of such integration.

Big Data, Improved Performance, and Fast DBMS

The number of data sources that companies want to analyze is constantly growing. The volume of calculations is also increasing. Therefore, BI systems are increasingly required to move to more productive work models. Among the general trends characteristic of the Russian market, it is worth highlighting the massive desire for the introduction of meta-languages ​ ​ and the modernization of the BI architecture, which allows you to unify the connection of visualization tools to any data storage and transfer the most complex procedures (including AI elements and dynamic analytics capabilities) to the user level BI.

In addition to the development of such areas as self-service and collaborations of Russian players to provide comprehensive BI tools, including data collection, storage, management and visualization tools, today there are trends aimed at lowering the threshold for entering BI and expanding the scope of business intelligence tools. Russian BI developers, following world leaders, are engaged in the creation and development of meta-languages ​ ​ that allow calculations at the level of the BI system itself, and not storefronts or data storage. A platform such as Visiology has already succeeded in this, which this year received its 3rd global update. The advantage of this approach is that at the BI level, the user can independently solve complex problems without resorting to the help of developers and programmers, - said Samir Ilyasov, Director of Development of BI and RPA "First Bit"

Another indicative direction of BI development is related to data storage. This is a transition to more flexible solutions that can work with a whole range of data stores. Thus, most of the products of Russian developers work with an open one, DBMS PostgreSQL but the Big Data column that has already proven itself on many projects has recently gained more and more popularity. ClickHouse DBMS The potential efficiency gain from moving a data warehouse to an open platform created Yandex is large enough. Therefore, today ClickHouse the developers JetBI, Visiology, Delta BI, Insight and a number of other platforms have already announced support and even integration. In addition, the developers mention plans for integration with Greenplum,,, Arenadata SAP SAP HANA BW and others, which DBMS will allow integrating new BI platforms into existing IT environments with minimal costs.

The situation with advanced analytics is changing - this has been said for several years, but only now we are moving from words to deeds: we see real cases for forecasting, solving optimization problems. At the new level, the tasks of industrial BI will be solved: as large-scale projects are implemented to digitalize the main processes in industry (digital factories, digital deposits), the introduction of more modern, powerful and intelligent BI systems will be required. In 2022, we launched FlyBI light business analytics product on the market, it is designed for Self Service tasks and is able to close the niche of Qlik and Tableau that have left the market. We focused on providing users with a really convenient and simple tool to work with heterogeneous data sources: easily combine them into a single data model, add their own sources if necessary, and build visualizations. FlyBI is designed to solve a specific problem that has arisen "here and now," when you need to quickly connect data from various sources and analyze them, investigating and "spinning" data from different sides in arbitrary sections. At the same time, our new product allows you to work with large amounts of data - the system processes up to 200 million lines per second, - notes Yulia Kudryavtseva, director of strategic development at Forsyth

Advanced Analytics and Voice Assistants

One of the trends in the development of Russian BI is the introduction and further development of intelligent technologies. Vendors are already using machine learning technologies to analyze data and generate requests. And judging by the developers' plans, this practice will only gain momentum.

Natural LanguageProcessing is developing. The global NLP market was estimated at $10 billion back in 2020, and is projected to grow to $50 billion by 2026 at a CAGR of 25%. NLP reduces the gap between the BI system and the business user - this allows you to receive analytical information by asking questions in the format of a dialogue, for example: "Which product group was the largest growth in the last quarter?," Explains Albert Nurutdinov, architect of BI systems IT company "Jet Infosystems."

In fact, already now some Russian BI platforms offer work with voice assistants, but in 2023 we should expect both a significant expansion of this practice and the penetration of AI into other areas of BI application, for example, to study complex dependencies and detect deviations in real time.

2021: BI systems: technological trends and development prospects

BI business users need to get quickly and comfortably from point A, in which the user does not understand how to solve the problem, to point B, where its solution comes. And so that the BI system is as simple as possible, convenient and beautiful to work with, and what is not so important under its hood.

Everything is important for professional market participants: the design of the BI system, the understanding of what lies behind the beautiful picture, the built-in tools, the directions of development of ideas and functionality that dominate the market. Market experts commented on TAdviser the most relevant aspects of the evolution of technologies in the field of business analytics, but first, of course -. Gartner

Gartner on the modern BI platform

The compilers of the Gartner Magic Quadrant for Business Intelligence (BI) and Analytics, published in February 2021, identify two main characteristics of the modern BI platform:

• Easy-to-use functionality that supports the entire process from data preparation to visual exploration to analytical data generation
• Self-service and advanced user assistance.

Most of the expenses in the BI area are for cloud deployments, Gartner experts state, so the main cloud service providers are on the market. It is also argued that in the global market, large data visualization capabilities have become massive, so that according to this characteristic, BI systems differ little from each other. The differences have shifted to the use of machine learning (ML), artificial intelligence (AI) in the entire workflow - from data preparation to analytics generation and management decision-making.

And a little more about the terms of BI according to international practice.

Until recently, business intelligence systems were divided into two classes. The first is classic BI systems that require an IT specialist or professional business analyst to work. The second is interactive visualization business intelligence systems that are accessible and easy to use for any user (self-services BI).

Recently, Gartner introduced a new term - Augmented Intelligence. And a new benchmark for the development of BI systems was outlined - Augmented Business Intelligence (ABI). This is a new stage in the development of BI platforms, to which augmented, virtual reality and artificial intelligence have been added.

Technological trends

Among the main technotrends, most of our experts name: the evolution of BI systems from classic to self-service BI systems, the provision of business intelligence services for the cloud model (SaaS), the growing popularity of the low-code approach, the use of artificial intelligence (AI), machine learning ( ML) and a number of others.

So, according to Artem Grishkovsky, commercial director of Trusted Environment (Group of company Systematica), the company's clients are interested in advisory analytics, DSS functionality, that is, the ability to support decision-making, and mobility.

The point of view of Nikolai Bekhterev, CEO of Modus BI, is closer to global trends.

The main technological trends in the development of BI systems are associated with artificial intelligence and machine learning, which are used to verify, clean and enrich data (DQM), detect trends and patterns, the expert says. - There has been a growing interest in using hybrid data storage, including relational, column, in-memory databases and Hadoop Distributed File System (HDFS) as needed. Apache Kafka distributed streaming platform will be used more often to integrate various information systems

Alexey Vyskrebentsev, head of the Forsyth Solutions Expertise Center, among the leading areas of BI systems development, names the concept of self-service and low-code, hybrid data storage architecture (data lakes), and the use of column DBMS.

Increasingly, companies are using column DBMS to work with storefronts, which provide maximum performance on huge amounts of data, the expert adds. "And if earlier companies mainly used relational sources or MPP platforms (Greenplum, Vertica), software and hardware complexes (Teradata, Exadata), now the trend is shifting to such DBMS as Tarantool, ClickHouse, Cassandra, etc."

Sergey Shestakov, General Director of Luxms Group of Companies, among the main technological trends includes BI's deep integration with AI/ML tools - the ability to work with models based on machine learning. Another trend is integration with BPM systems and even more, providing BPM with functionality for managing key figure entry and negotiation.

Yuri Kolbasin, partner of the Digital Economy League, director of Big Data practice talks about the development of the direction of BI self-service systems, the integration of AI technology and machine learning, deep integration with Data Governance. All together this leads to the fact that reporting becomes targeted, that is, reporting information will soon be transmitted depending on the context and on the task that the user is currently solving.

Roman Dzvinko, Executive Director of the SPC, also speaks about the prospects of self-service systems (self-service), advanced analytics (ABI) as the main trends.

Another trend in the development of BI systems is MD/DQ (Master Data/Data Quality management). The importance of data quality and master data management is undeniable. After all, reasonable and balanced decisions can be made only on the basis of correct data, the use of inaccurate and poor-quality data can negatively affect business, he adds.

Svetlana Vronskaya, an expert at the analytical solutions department of Korus Consulting Group, confirming the relevance of independent work with BI (self-service) and augmented analytics, highlighted the technology of the Internet of Things (IoT).

Transmitting data from sensors using IoT is an urgent task. It is not always possible to first transfer data for processing to a centralized hub and only then to an analytical system. For example, in complex production or in mining. You have to immediately "stream" the data in BI and process it there. Therefore, all vendors will embed functionality for working with data from IoT devices/systems. The Internet of Things will require new skills from employees who work with analytics. Failure to train them in advance will result in companies being unable to use data from IoT sensors and losing efficiency, she adds.

Andrei Kharlak, technical director of Clover Solutions LLC, names among the trends that it makes sense to pay attention to: the development of technologies for managing metadata, that is, data data, the popularity of open source code for creating data collection, storage platforms and no-code tools. The expert is skeptical about the likelihood of revolutionary changes in BI thanks to AI in the near future. This will happen only after the developers of BI platforms learn to organically integrate AI into the decision-making process, that is, when AI will detect something, describe, find reasons, predict, prescribe, decide and, ultimately, act, the expert believes. Today, all this is already in an unmanned vehicle, but it is still absent in analytical systems.

In my opinion, now the key problem in working with data is technologies and tools to improve their quality. The solution to this problem does not keep up with the rapid growth in the number of sources and the volume of information. Data quality is holding back the growth of AI applications that need to learn from something. Even the best learning model is useless if it receives data with errors at the entrance, he adds.

The most noticeable trend according to Alexei Artemenko, regional director of Qlik Russia and the CIS, is the transition to the use of Solutions SaaS. The expert believes that by 2022, clouds will become an integral part of 90% of data and analytics innovations. In the medium term, critical systems migrate to clouds, followed by applications. In the future, SaaS will provide immediate access to new technologies - for example, augmented analytics. The second and third trends are strengthening the position of the BI-self-service, a new format for consuming visualizations and stories based on data storytelling.

Russian BI systems: is it still a classic or is it already a self-service?

Russian BI systems are diverse in functionality and implementation. But in general, so far they are only moving in their development from classic to self-service systems - this is the opinion of the majority of our experts. At the same time, there is no clear distinction between "classics" and self-service on the market. The following point of view is also presented: even advanced Western BI-systems, which belong to the category of self-service, require the involvement of IT specialists to create a basis for the independent work of business users.

Russian self-service solutions for data management today are only at the stage of active development, says Nikolai Bekhterev, Modus BI.

The trend from classic BI systems to self-service is one of the main ones when there is a shortage of IT specialists and advanced analysts with PythonSQL knowledge//R in the market. visualization of data Most Russian BI systems have designers for. However, low-code data collection and processing tools (ETL/ELT), as well as model and data set designers, are not available in all domestic BIs, he adds.

Visary BI Dashboards Designer

Roman Dzvinko, SPC "BusinessAutomatics," states that the Russian market for BI-systems is quite diverse, it presents both classic solutions and self-service systems, but the trend towards self-service will gain momentum and over time most vendors will offer self-service BI. Yuri Kolbasin, "Digital Economy League," mildly notes that many manufacturers of Russian BI systems understand that self-service is an integral part of any modern business analytics system and "try to implement" this.

Alexey Vyskrebentsev, "Forsyth," believes that self-service solutions can still be "counted on the fingers." Artem Grishkovsky, Trusted Environment (Group of company Systematica), speaks out tougher: most Russian BI solutions can be safely attributed to classical systems.

Alexey Petunin, SAP CIS, notes that today you still cannot do without an IT specialist, since any analytical report contains a data source - for example, a storefront in storage, and a business user cannot always independently prepare it.

As a rule, even with self-service BI, data for the user's independent work in the visual designer mode of diagrams is initially prepared by the IT specialist. Therefore, in the Russian market now you can find either an option when the IT unit is fully preparing the report, or a hybrid model, when the IT unit is preparing the source, model and semantics of data, and the user is already independently constructing the report, it adds.

The border between classics and self-service is determined not only by the functional features of BI solutions, but also by the organizational and role structure of the project implementation team, - Rustem Ibragimov, Deputy General Director of BARS Group, is convinced. And the more projects are implemented with the active participation of end users, the more confidently the solution being implemented can be attributed to self-service BI. The expert also focuses on a hybrid approach, a reasonable compromise between classics and self-service.

The demand for democratization of data analysis tools has become not just a trend, but also a significant factor in choosing a BI solution, the expert states. - At the same time, atypical tasks continue to be encountered on projects, which are not closed out of the box and require the participation of an integrator. This specificity of project implementation requires hybrid products from vendors, combining both simplicity and flexibility. A similar situation is found among our colleagues in the market, so I think that most Russian BI systems are in a state of common compromise between classical and self-service analytics systems

Andrey Harlak, Clover Solutions, states that today self-service is no longer the opposite of traditional BI, since all modern Western BI platforms allow working with data in self-service mode. But self-service is not always required and not all employees, it is just another way to work with data.

Andrey Dyukov, Head of Sales and Development at Netrika Medicine, recognizes the importance of self-service functionality, focusing on the specifics of the healthcare sector.

In the field of health informatization, it is difficult to make a division into traditional BI and self-service systems, says the expert. - The independent work of a specialist on the spot is definitely important, since no company is able to quickly respond to the requests of the public healthcare sector, always going on yesterday. Organizations subordinate to the regional Ministry of Health must have a sufficiently flexible tool to implement tasks without involving a vendor

Svetlana Vronskaya, KORUS Consulting, notes several "but" in the work of business users in self-service mode.

Many users simply do not know how to handle the source data, and not all companies have provided opportunities for teaching these skills, the expert explains. - And another controversial point to consider when implementing the BI self-service system: there is a danger that users will start creating their own analytical applications to solve their tactical problems, and not act within the framework of a single data strategy

Dmitry Sysoev, director of the management consulting and BI department of the company Norbitol (group LANIT""), classifies not only Russian BI, but also advanced Western solutions as classic, since even they often cannot do without serious architects and developers. Users are able to create forms themselves, but this is possible only on a good basis, which should be created by high-level specialists.

Augmented Analytics Outlook

Augmented Business Intelligence (ABI) involves the use of AI and machine learning, a new level of user interaction and BI-system, including processing requests in natural language. The term itself was introduced by Gartner relatively recently.

ABI - the next step in the development of business analytics or the game of terms? What is the advantage over classic BI? Is it still the future or is it already the present? Here are the questions that we tried to clarify from our experts, which can be very conditionally divided into skeptics and optimists.

Artem Grishkovsky, Trusted Environment (Group of company Systematica), believes that ABI is a synthesized term to determine a new trend, and machine learning (ML) and artificial intelligence (AI) are just mathematical models. And almost all industrial BI systems have tools for building such models. They may be useful for solving a specific customer application, but it makes no sense to mention them in general terms. The point of view of his colleague is supported by Alexey Vyskrebentsev, Forsyth.

From our point of view, this is not a new trend. This is rather a new marketing name for the trend, which combines several existing classes of solutions in the market, "he says. - As to the advantage of ABI over classic BI, it is to move from historical value analysis to data-driven business transformation

Yuri Kolbasin, Digital Economy League, adheres to a slightly different point of view in this matter. He is confident that in the era of big data, it is ABI that will be the next step in the development of business analysis systems.

Analyzing the huge amounts of data that large companies have is a very difficult task, "the expert argues. - Highly qualified employees are needed to solve it. ABI using ML/AI will simplify the preparation of data, search for an insight in it, help to quickly test hypotheses, as well as find reports on the questions posed without involving a specialist (data scientist) for routine tasks

Alexey Petunin, SAP CIS, states that advanced analytics includes speech recognition capabilities, when the user asks a question in a voice and receives an answer in the form of graphs, predictive models, voice assistants that help build automated reporting. Most of the company's products, the expert notes, initially contain such tools.

The vital relevance of the new term is confirmed by Alexander Trifonov, head of analytics at the I-Teco system software solutions department. It testifies to regular requests for AI (AI) and machine learning (ML) tasks. And he gives an example: the appeal of several domestic banks this year with a request to develop a solution in order to identify the root causes and predict possible problems in the IT infrastructure. And even gives a special term for such tasks: AIOps (Artificial Intelligence for IT Operations).

A distinctive feature of such solutions is streaming data from various monitoring systems and the use of machine learning in real time, which significantly increases the chance of a proactive response to a possible simple business, the expert says. - In our opinion, it is the work in the stream and close to real time results for decision-making that are the main advantage of ABI over traditional BI

I agree with my colleague and leading consulting companies on the prospect of ABI Maxim Ozerov, director of analytics projects at Navicon. He considers augmented analytics one of the tools for improving literacy and the level of culture of working with data. With the help of built-in machine learning tools, processing natural language requests, more and more people are beginning to expect from BI systems not ready-made canvas reports and difficulties in developing them, but interactivity and democracy. He states that today the ABI functionality appears, first of all, in Western cloud products, which have the ability to "roll out" new functions to a large number of users at once.

Svetlana Vronskaya, KORUS Consulting, states that augmented analytics technology is just beginning to develop, but so far this approach carries the risk of data leakage. The expert also recalls that the Gartner researchers themselves calculated pessimistically: by 2022, augmented analytics will be used in full by only 10% of analysts. This means that the ABI capabilities will last even longer before the general user.

Alexey Artemenko, Qlik Russia and CIS, believes that the future lies with ABI technology, since this is a completely new level of interaction with data. All new developments in the BI industry are now aimed at reducing the time from receiving data to insight, he recalls. Augmented analytics technologies help you work faster with data.

For example, the user only downloaded data from the source. He has not yet built any visualizations, but he can already communicate with the BI system in chat or voice, get a visualization of the necessary data automatically generated using AI, the expert adds.

Alexey Arustamov, Loginom Company, notes classic BI - this is either a "post-mortem analysis," or an attempt to see patterns in a huge dataset, which is incredibly difficult without the use of artificial intelligence (AI) and machine learning (ML) technologies.

The main goal is to look forward, and there is no way without modeling or forecasting methods. What can you see in big data when it comes to hundreds of millions of records? Nothing except for some "egregious" emissions or general trends. Everything will be aggregated and averaged, and the most interesting thing is nuances, non-trivial patterns

Andrei Dyukov, Netrika Medicine, very succinctly and capaciously expressed himself about the present and future of ABI technology: Шаблон:Quote 'This is our future, you need to remember this and work with this thought.

Cloud BI services in the Russian market

So, in the world, most of the companies' spending goes towards BI cloud deployment, as evidenced by Gartner. Cloud BI services are not yet presented on the Russian market and the demand for them is small - this is how our experts see the situation. This is hindered, firstly, by regulatory barriers when it comes to global cloud providers. Secondly, Russian customers, according to our experts, still do not trust the clouds, prefer BI systems on their site. At the same time, many experts see that the demand for cloud services is growing, especially in the SMB segment, and some even state the presence of a large demand for cloud BI analytics.

Alexey Vyskrebentsev, "Forsyth," states that in this regard the Russian market is against Western trends. If we talk about the analysis of corporate metrics, then Russian companies are almost all trying to choose solutions on their site, which is dictated by regulatory restrictions - both at the level of the companies themselves and from the point of view of Russian legislation.

Now there is a movement towards the use of cloud infrastructure, but everyone chooses protected data centers located on the territory of the Russian Federation. And from the BI point of view, such a trend is likely to be only in SOHO/SMB segments. Again, if a medium or small business is mature in terms of data use, then they will not choose a cloud solution. The most famous solution on the market is Yandex DataLens, but it also cannot boast of a wide range of tools.

Alexey Petunin, SAP CIS, states a great demand for cloud platforms. Due to the current restrictions on the use of cloud infrastructure outside Russia, the company offers Russian customers an approach when only the semantics of the report are stored in the cloud, and productive data does not leave the corporate landscape.

The demand for cloud platforms in the Russian market is growing, as Svetlana Vronskaya notes, KORUS Consulting. BI systems are becoming popular not only with large businesses, but also in the SMB segment, and these enterprises often want to avoid costly investments in additional infrastructure and support for a new information system.

There are many solutions for business analysis in the cloud version on the domestic market, so customers can only choose a system that suits them, it adds.

The situation with cloud BI services and Maxim Ozerov, Navicon, who believes that cloud platforms for business analytics are already quite widespread in the Russian market, seems optimistic. In particular, more than half of all new BI projects of the company start in the cloud. At the same time, the components of the solution often "move" gradually: first visualization and mobile analytics, then analytical models and only then directly data stores.

We do not see much difference in this regard between Russian and global companies - the transfer of BI to the cloud depends more on the priority of CAPEX or OPEX expenses, as well as on the degree of openness of management, he adds.

Rustem Ibragimov, BARS Group, states that the trend towards clouds continues to gain momentum, which is especially important for small businesses with small IT budgets, where there are no specialized specialists in the state to administer solutions on the ground. At the same time, there is a certain skepticism about the SaaS model from medium, large businesses and government customers, which is associated with distrust in terms of protecting information stored on the cloud infrastructure. At the same time, the expert notes that with the functional development of BI solutions based on the SaaS model and the emergence of successful cases of working with large customers, the market for cloud analytics platforms will grow steadily.

BI Design Approaches

It is impossible to make a modern user work in the system if the design of the program is ugly, ill-conceived in terms of ease of use or seems to him as such. The task of creating a beautiful and convenient design is not only aesthetic, with color and shape, font size and location of workspaces on the screen, it has a number of technological aspects.

Nikolay Bekhterev, Modus BI, states that the UX/UI approach is primarily relevant, that is, building a design based on knowledge of user experience and behavior. At the same time, visual display of data should be available from any device, so adaptive layout technology is relevant. The ability to control colors/fonts, pop-up windows is important for the user in self-service tools. Among other things, you need to offer ready-made interface themes, palettes for diagrams, as well as the ability to save user settings.

Screenshot of the Modus BI system

For the development of the enterprise ecosystem, an important technology is the technology of embedding dashboards in other programs using Single Sign-On (SSO) authorization and providing security using flexible configuration of data access restrictions (Raw-level security, RLS). The reverse technology is also relevant, that is, embedding ready-made visualizations into a BI product using API access and data request management, the expert adds.

I agree with the paramount importance of the UX/UI approach to design Andrei Harlak, Clover Solutions. He cites UX as a key factor in the proliferation of analytics within the company and the emergence of analytical culture. If users do not succeed, there is a risk that they will return to well-known Excel tables, or even refuse to use the data in their work.

The point of design and UX in the case of analytical applications is that we must reduce the distance from data to decision making. The key question is how easy it will be to turn what we showed on the graph into some kind of conclusion, insight, or into a solution or initiative, how easy it is to test some hypothesis, the expert says.

Alexey Petunin, SAP CIS, draws attention to the International Business Communication Standards (IBCS), which are practical proposals for the design of reports, presentations, dashboards, as well as the charts and tables contained in them. The fact is that if you choose neutral colors and shades, the user ceases to subconsciously focus on them and focuses on numbers and diagrams as a reflection of the result of his work. It also affects his emotional background, confidence, attitude towards the product itself.

Many analytical products are now available for test access, says the expert. - Such openness on the part of vendors, this is also a big step in working with the consumer's perception of their products, because he receives not some stripped-down analogue, but a full-fledged version of the product and is limited only by the time frame for use

Very brief and specific in his opinion on this issue Alexey Arustamov, director of the Loginom Company: {{quote 'everything in the browser is the main trend, minimalism in design - the simpler the better. }}

"Storytelling" in BI systems

Analytics involves research to find answers, and "storytelling" - creating stories based on data storytelling - is based on knowledge of the answers, their beautiful presentation in order to change the way the audience makes decisions.

Many Western BI systems have built-in tools for creating such stories. The storytelling process resembles the creation of presentations: screenshots are taken with the output data, text blocks are prepared, libraries of templates of typical stories and visual effects are involved. In some Russian analytical systems, such tools also appear, our experts note, but the degree of its demand is different.

Roman Dzvinko, BusinessAutomatics, states that compiling stories based on data using a BI system is a useful practice and a popular format for submitting information.

Data storytelling technology allows you to competently and clearly talk about the study, and students will be able to make business decisions more efficiently. This functionality is already present in some Russian BI systems, he adds.

Data visualization is a very interesting area, but domestic customers are not thinking about it much yet, says Alexey Vyskrebentsev, Forsyth.

Usually, customers choose a visualizer so that it is readable and shows the data structure in some way, but do not think about why they chose this particular visualizer, specifically this structure of dashboards, he adds.

The storytelling format is in great demand, notes Alexey Petunin, SAP CIS. When displaying a report from the audience, they can ask a question by any number. A presentation prepared on the basis of data allows you to immediately, on the screen, show where this or that value came from, compare it with an average or similar indicator for any necessary period. In fact, each figure has its own story. To create it, systems use a set of screens, superimposing reports on top of each other, applying various filters, and much more.

The ability to tell stories based on data can be an important tool for disseminating a data culture within an organization, says Andrei Harlak, Clover Solutions. So far, this toolkit is rarely used, he states, because the tools built into BI systems for creating stories based on data are primitive. The speaker suggests that this functionality of BI platforms will develop, because business today has difficulties with the spread of data culture.

Alexey Arustamov, Loginom Company, briefly states that the company did not encounter customers requesting such functionality.

Natural Language Query Processing

Most experts have described natural language query processing technology as interesting, but not yet mature enough and little common.

Even Alexey Petunin, SAP CIS, who spoke about the already working functionality of speech recognition in the company's cloud systems, admitted that, although customers have an interest in this functionality, technologies still need to be developed. In particular, the voice assistants he mentioned earlier are still far from the full-fledged functionality that customers would like to receive.

There is no doubt that this technology will develop in the future, Nikolai Bekhterev, Modus BI, but today the tools are in the experimental stage and are not used everywhere.

Speech recognition is a very expensive solution that few companies can afford, says Alexey Vyskrebentsev, Forsyth. He expresses the hope that with an increase in the quality of transcribing, technologies will become cheaper, and then such solutions will be more in demand and widespread. The Forsyth company has developments and even examples of such implementations, but this is still a "piece product."

Andrei Kharlak, Clover Solutions, draws attention to the economic efficiency of the introduction of the technology.

So far, no one has found an answer to the question of how the processing of natural language requests will pay off. It looks cool, but ROI cannot count. Probably, if the manager could voice ask the BI system the same question that the analyst answers to him today, he would prefer communication with a soulless BI system. But so far, analytical systems do not have the functionality of this level of maturity

Alexey Arustamov, Loginom Company, notes that the main problem of technology is the ambiguity of words.

In most cases, it is difficult to answer even simple questions - for example, who should be considered a client? It's not as obvious an entity as it might seem at first glance. Natural language query processing implies that ambiguity will somehow be solved, but this is not at all just without understanding semantics and the subject area

Categorical Artem Grishkovsky, "Trusted Environment" (Group of company Systematica): {{quote 'The technology is underdeveloped, and it is not entirely clear why it is needed, since the conclusion can be meaningful when the algorithm for obtaining it is clear. If the algorithm is clear, then "cry" it or "talk" - there is no difference. Natural language queries, 3D visualization, chatbots, etc. - this is all not about analytics and BI }}

Streaming (streaming) analytics

The data is usually saved first and then analyzed. Streaming (streaming) analytics involves analyzing data in the stream, as it arrives and before it is saved. Experts call a number of tasks when streaming analytics creates additional value, one of them is when the fastest reaction is needed, because any delay will lead to catastrophic consequences (failure of critical equipment) or large security problems (cyber attacks, fraud) and others.

With the spread of column DBMSs and IoT platforms, this trend is becoming clearer, as Alexey Vyskrebentsev notes, Forsyth. Streaming analytics used to be in demand by only a few, and the size of the temporary array that was rendered was small. Now the situation has changed, in particular, the cost of iron has fallen, so companies accumulate arrays and visualize data on the fly. Real-time analytics is required to solve various classes of tasks, for example, to monitor the state of the network or the state of the equipment.

Streaming analytics is one of the necessary technologies in the world of an ever-growing volume of data that carries value in its volume and totality, says Artem Grishkovsky, Trusted Environment (Group of company Systematica).

Mobile Business Analytics

Mobile analytics, that is, access to a number of analytical system capabilities through a remote personal device, is present in many BI systems as an addition to the basic functionality. The degree of demand depends on the specific company, but it is most often used in large companies.

Mobile Analytics in the Forsyth Solution

Alexey Petunin, SAP CIS, notes that today almost all BI tools have a mobile analogue, and for different operating systems. It is convenient for users when the screen automatically scales to a specific device, be it a phone, tablet or laptop. Requests for mobile analytics come from different levels of users: top management, line employees, heads of departments.

The prospects for the development of this area in Russia strongly depend on the spread of mobile technologies and an increase in the coverage of cellular communications and the Internet. The faster and more actively they develop, the more opportunities mobile analytics has, "he adds.

Andrei Harlak, Clover Solutions, states that mobile analytics is used. According to him, it is advisable to send only notifications from the analytical system to mobile devices.

I disagree with my colleague Dmitry Sysoev, NORBIT (LANIT), he believes that mobile analytics are being used more and more often. But rather as an addition to the basic functionality, in order to quickly receive general information on personal devices at any point. Moreover, this applies mainly to a variety of summaries and upper-level general indicators, for a detailed analysis of mobile applications is not enough.

Yulia Kudryavtseva, "Forsyth," considers the main problem of mobile analytics to be the requirements of the security services. When taking corporate information outside the corporate circuit, appropriate security tools are needed - encryption at the level of the operating system, application, device, network, and if everything is done at the proper level, it will not be cheap.

Predictive (predictive) analysis

About predictive analysis, the range of opinions among our experts turned out to be large: from "not in demand" to "very in demand."

Artem Grishkovsky, Trusted Environment (Group of company Systematica) believes that predictive analysis is still not in demand, since there is no base - verified data in the required amount.

Predictive analytics is still a special case, the results of which are viewed as "pranks." First, BI should have a system of technologies that provide confidence in the data. Second, a powerful, understandable toolkit for industrial modeling and forecasting on a large volume of restrospective data

Roman Dzvinko, SPC "BusinessAutomation," disagrees with this thesis. He notes that predictive analytics are quite in demand, as it increases the competitiveness of the company by owning predictive information that can be operated to quickly make the right decisions. The main predictive analysis tools are: data collection, their exploratory analysis, and predictive modeling.

Alexey Vyskrebentsev, Forsyth, also speaks of the great demand for predictive analytics, while noting the different degrees of maturity of companies regarding its use. The expert listed the stages of this maturity: analysis of historical data, search for business insights, business optimization, data monetization, data-based business transformation.

Starting from the second stage of maturity, companies use tools of varying degrees of complexity, for some tasks basic tools are enough, at the level of primary mathematics. For example, if the value is above a certain threshold, then you need to send a notification. It is important to realize that BI is not "about pictures," but to speed up decision-making, so that as little time as possible is spent from the moment of receiving data to the moment of making decisions, the expert explains.

Clients are constantly interested in predictive analysis, says Alexey Petunin, SAP CIS, and requests come from different industries. Today everyone wants to understand where this or that figure came from and what it can be tomorrow. This is necessary to take proactive action, gain competitive advantages and improve business efficiency.

But now many customers expect the emergence of an advanced interface in the analytical system, where there is a certain set of parameters that the user will choose, and the system itself will build a model and give a forecast based on it, he adds. - In my opinion, this hides great potential for the development of BI systems so that the end user can work in the future with predictive models on his own

Rustem Ibragimov, "BARS Group," recalls that predictive analysis has a powerful potential, but its use is a difficult task. This is a set of tools with a number of limitations and assumptions that require, firstly, enough quality data and an understanding of the nature of this data. Secondly, a competent team of specialists (data scientist) is required, who know how to interpret business problems in the language of the mathematical apparatus and have experience working with a set of specialized IT tools. Customers who understand this specificity and consciously suitable for solving relevant business cases will be able to take advantage of the potential of predictive analysis, the expert believes. But to expect predictive analysis to "do magic" with an arbitrary set of tasks is far from true.

Шаблон:Quote "Most BI systems are developing towards integration with industrial standards of predictive analytics tools that have been actively developed in the open-source community," the expert adds.

2020

A survey of experts from the Russian BI market and a further analysis of their answers showed that three key trends prevail in the field of business analytics in Russia as of autumn 2020 - this is an increase in the demand for domestic systems, including thanks to import substitution policies, an increase in the number of cloud solutions and the use of artificial intelligence and machine learning technologies in BI tools. Market participants talk about these trends most often.

Increase in the share of domestic systems

Many Russian companies choose Russian solutions in connection with the import substitution policy. This can be either an implementation of the tool from scratch or a replacement or extension of the current BI solution.

In any case, customers carefully test and study the products of Russian vendors both in terms of the convenience of business users and the performance of the solution, "says Yegor Osipov, head of Big Data at CROC IT company.

Ivan Vakhmyanin, CEO and co-founder of Visiology, also notes an increase in the share of Russian software due to the trend in import substitution in large and state-owned companies. At the same time, in his opinion, the demand for domestic solutions is due to the fact that medium and large businesses want to keep analytics inside their IT perimeter, and not in the cloud, while most popular foreign BI tools have either completely gone to the cloud, or provide on-premium version with lagging functionality or at high prices.

Increasingly, Russian BI platforms appear in the project shortlists of vendors along with the leaders of the Gartner quadrant, - confirms Aleksander Dmitriyev, Operations Director of the Ctrl2Go Group (ControlTuGo. Ru).

Rustem Ibragimov, Deputy General Director of BARS Group, adds that domestic vendors are creating partner unions designed to functionally strengthen their solutions and expand the audience of consumers.

The first marketing research has begun, professional communities are being created, meetings are being held - in general, one can note the desire to generalize experience, he notes.

At the same time, large companies, having quite large financial resources, are seriously thinking about creating their own expertise and platform solutions. Entire ecosystems are emerging, as well as products that companies create not only for "internal" needs, but also for sale on the open market.

Many large companies have similar plans. Such companies perceive the import substitution process as a new point of business growth, and not a way to change Western software to domestic software, - said the Alexey Vyskrebentsev head of the center for solution expertise. Forsythe""

Demand for Cloud Solutions

The BI systems market and the cloud trend did not bypass. Such technologies are in great demand today, as cloud solutions relieve business of both the headache of optimizing spent funds on licenses and physical storage. All-in-one cloud BI systems make available BI tools not only to large corporations and holdings, but also to most small companies and public sector organizations.

In 2019, 90% of users worked with business intelligence tools on a subscription basis, according to Drenser. This is due to the fact that BI systems are demanding on the performance of servers, the cost of licenses of which stimulates the increasing use of cloud technologies, explains Aleksander Dmitriyev, Operations Director of the Ctrl2GO Group.

The demand for BI-solutions of the "lightweight" class among small and medium-sized businesses (especially production) and public sector organizations over the past 2-3 years has grown by an order of magnitude. Accordingly, the supply market is responding to this challenge with the rapid growth of all-in-one cloud solutions. Such solutions, as a rule, have good usability characteristics that do not require the deployment of their own complex infrastructure and allow solving typical data analysis problems at the level of ordinary users, - said Alexey Baryshkin, an expert on digital interaction between government and business at Netrika.

However, this trend is much less noticeable among large businesses.

Large corporations are trying to own digital platforms and increase their competencies - this is their strategic asset, - explains Sergey Shestakov, CEO of the Luxms Group of Companies.

Application of artificial intelligence elements

Another important trend is the integration of artificial intelligence (AI) -based tools into BI solutions. What was exotic a few years ago is now becoming standard functionality.

Andrey Krasnopolsky, CEO of the ATK Consulting Group, notes that the introduction of AI technologies and machine learning (ML) in BI tools allows you to simulate and track decision-making processes.

Alexey Artemenko, regional director Qlik Russia and CIS, adds that artificial intelligence is used to process data and automate insider searches in data.

At the same time, the operating director of the group, Ctrl2GO Aleksander Dmitriyev, notes that the use of advanced analytics tools (the introduction of ML and other elements of AI) within the BI system is most often found as a pleasant addition, and not the basis of the functionality of systems.

According to him, at present, the predominant majority of BI systems implementation projects in Russian companies have no other goals than automation of reporting and data visualization.

Data democratization

One of the key trends in the BI market over the past couple of years has been the democratization of data. If five years ago BI systems were introduced for a group of analysts and top management, now more and more companies are coming to an awareness of the value of data and competent decisions made on their basis.

As noted by Alexey Artemenko, regional director of Qlik Russia and the CIS, a business analyst from the "sacred knowledge" available to several dozen people in the company, turns into a tool for the daily work of employees of different departments and management levels, supporting decision-making.

This is confirmed by the experience of our clients such as Sberbank, Rosgosstrakh, Gazpromneft, who have scaled BI solutions for thousands of employees throughout Russia and the CIS, with a well-thought-out training system and the integration of analytics into business processes, - he explains.

Alexey Vyskrebentsev, head of the Forsyth decision expertise center, adds that the trend towards "democratization" of data is now at its peak.

Corporate business processes have become very dynamic. Companies want to expand the work of business users with data through the capabilities of Self-Service BI. On the other hand, the trend is supported by Data Science specialists who know how to work with data platforms and know the business logic of the enterprise, the expert adds.

Achieving the BI Plateau

Dmitry Savvin, architect of BI solutions of Qlever Solutions, believes that if you look at the final analytical applications of market leaders, then their capabilities are equal. Today it is difficult to come up with something new here and even the available functions are sometimes redundant, the expert believes.

We are increasingly seeing the so-called "BI plateau." There are many tools, the possibilities are huge, but employees lack the ability to extract something useful from the data. This inhibits the spread of analytical culture within companies, and a huge part of the functions of analytical applications remains unclaimed. We can say that today the technical capabilities of applications overtake the organizational abilities of companies, "says Dmitry Savvin.

Developers of analytical platforms are trying to solve such a problem by embedding in their products hints of what the analyst or manager should look at. These clues can use machine learning and take into account the experience of other companies. Another way that vendors offer to exit the BI plateau is the ability to communicate with the analytical system in natural language (NLP, natural language processing).

However, we see much greater potential here in alerts that come to a mobile phone and help employees working at points of sale act, and managers control them, "explains the architect of BI solutions Qlev Solutions.

Other trends

Participants of the domestic BI market interviewed by TAdviser talk about other trends. Aleksander Dmitriyev, Operations Director of the Ctrl2GO Group, talks about the ongoing trend towards combining various data sources, such as business applications and data on the operation of physical units, collected using sensors, which is relevant for companies with a high information density of the value added chain (production, logistics, production), as well as for servicing heavy and expensive equipment.

Also among the trends, he highlights neural networks and machine learning, which are necessary for testing various scenarios. This, he said, allows you to detect hidden patterns and affects management decision-making.

Roman Dzvinko, executive director of the SPC "BusinessAutomation," is among the trends in mobile analytics. According to him, it is on an upward trajectory due to the optimization of the work of tables, graphs, visual representation of data, OLAP functions on touch screens of mobile devices.

{{quote 'Mobile business analytics allows company executives and other business users to carefully analyze a huge amount of information through their mobile devices and turn the result of such analysis into verified management decisions, ensuring that all, especially remote employees, will have round-the-clock access to the necessary data anytime and anywhere, - says Roman Dzvinko. }}

Ivan Vakhmyanin, CEO and co-founder of Visiology, talks about two more trends:

• The growing popularity of open-source solutions in data storage, data transformation systems (ETL) and advanced analytics.

We couldn't get past this trend and released the free, open-source ETL tool ViXtract based on Python. At the same time, in the field of data visualization, automation of reports and manual entry (solutions for consolidation and planning), on the contrary, the positions of proprietary tools have only strengthened, he notes.

• Convergence of data processing of various scales.

Now it is already normal when one BI system processes both Big Data (due to direct convectors to analytical MPP DBMS), and the usual volumes of data in In-Memory, and small, but complex in structure and quality data downloaded from Excel or received by manual input, - explains Ivan Vakhmyanin.

Rustem Ibragimov, Deputy General Director of BARS Group, speaks about the trend towards the development of internal expertise related to data analytics among customers.

We are seeing the creation and development of data offices. Many of them started as project teams that worked with external contractors for the implementation of analytical tools and continued their development as separate units that solve a wide range of data tasks, "he says.

Another trend, he said, is associated with the development of non-profit analytics. For example, during the quarantine period, many resources appeared on disease analytics. There is an increase in interest in the so-called "social" data, which are stored by the state and are associated with the life and development of society itself. There is a kind of socialization of BI - these data do not have such a commercial profit, they are simply interesting to people and are published using BI tools, says Rustem Ibragimov.

The global trend is software development without writing scripts. Engineers think over all the necessary actions for the user.

We are developing our product "Forsyth. The analytical platform "along this path is minimizing development, maximum customization," says Alexey Vyskrebentsev, head of the Forsyta solution expertise center.

Alexander Elin, CEO of Alan IT, among the trends includes services that are easy to use, ready for implementation and use

The overall uncertainty and dynamism of the markets in which customers operate has a strong impact. If earlier companies were set up to develop individual projects and were ready to wait several weeks and even months, now there is a clear desire to get a solution with small time and financial costs, he notes.

Yuri Efarov, CEO of Sapiens solutions, lists several other trends:

• Most of the tasks of BI in the current and last 2019, in essence, were Big Data tasks, which imply either high complexity of the problem (integration, calculations, real-time), or ultra-high volumes of processed data.
• Customers are discovering a desire to systematically approach the construction of corporate BI. The complex of BI tools in a modern company, in their opinion, should cover the entire range of analytical tasks - from reporting and building informative visualizations to deep processing of data and searching for insights. Previously, all these tasks were looked at separately. Customers are also focused on finding a balance in the cost of storing data, on the one hand, and the speed of processing it, on the other.
• In the context of solving business problems, customers are ready to change the BI products and vendors used to alternative options, ready to expand the set of tools used to cover current business tasks.
• An increasing number of BI projects are being made with the subsequent goal of using advanced analytics and ML models.
• The course on self-service BI tools continues. However, in fact, the use of self-development tools is still low.
• Embed analytical tools and calculations performed using them as steps in key business processes.
• Customer commitment to real-time analytics tools for ad hoc queries and faster data acquisition.

Dmitry Savvin, the architect of BI-solutions of Qlev Solutions, considers the change in customer requirements to be a key trend. Although the volume of analyzed data is growing rapidly, and new and new sources are constantly connected to the BI system, customers want to receive ready-made information faster.

The second trend, according to an expert at Qlever Solutions, is associated with the use of Python and open frames in projects that help organize data management.

Today, it is difficult, wasteful and ultimately pointless to solve all problems, limiting itself to one platform and tools built into it, he believes.

Dmitry Savvin also notes the interest of customers in products that solve some kind of business problem "from and to." For example, solutions for pricing, for segmentation of consumers, services based on geoanalytics.

A product for any one function can be developed on any platform - on Qlik, Tableau, MS Power BI, using Python and ready-made libraries for rendering. It is only important for the customer that he is given a ready-made tool, which is already used in other places and the practice of use has developed around him, - he explains.

Svetlana Belous, business development manager at Navicon, answering a question about trends, noted that the company's clients, including many representatives of the pharmaceutical market, FMCG and CPG companies, are interested in predictive analytics. They are interested in obtaining forecasts with a high degree of accuracy and detail, so that they can then be used to plan production and sales, as well as to reduce out of stock and improve customer service.

In addition, Navicon sees interest in client analytics. Companies seek to study what they know about customers, analyze this data, in order to find the audience most loyal to the brand as a result, and promote their products among them.

Another trend is the desire to analyze the return on investment in different channels of promotion and redistribute funds depending on the conclusions and insights obtained using analytical systems. This includes, for example, trade marketing analytics, which allows you to calculate the effect of a promo.

Alexey Baryshkin, an expert on digital interaction between power and business at Netrika, believes that the most noticeable trend is the deeper penetration of BI solutions into market segments, where this class of solutions was previously presented as redundant or excessively expensive. First of all, this phenomenon is typical for small and medium-sized businesses (especially manufacturing) and public sector organizations.

Artem Grishkovsky, Commercial Director of Triaflai (Trusted Environment, part of the Gro up of company Systematica), believes that the public sector, which has a huge array of data, has ample opportunities to use BI technologies

One of the important areas of application of BI platforms is the creation of integration solutions for state and regional authorities, including within the framework of the implementation of a number of regulations adopted at the state level. Based on the need to implement these tasks, development plans and IT budgets for 2020 were adopted, he explains.

According to Artem Grishkovsky, the full use of BI as a decision-making support tool hides a huge potential for industrial enterprises and management companies, which allows creating digital business models, monitoring the current state of business, making decision-making more transparent and predictable, reducing inappropriate costs, planning investment directions and the effect of them. The largest holding structures of Russia are already aimed at building digital business models, he says.

As for other industries, according to the Triaflai expert, BI technologies make it possible to fully implement the advantages of a customer-oriented approach in the work of enterprises in the service sectors. This is already visible today by how the assortment of goods is changing, new services appear. In finance, BI is a big data analysis tool for creating new products, identifying threats, and analyzing risks.

What's New in BI Systems

In the coming years, the tools and functionality of data analysis systems will develop taking into account the growing needs of enterprises in streaming analytics, "democratization" of business analysis, maximum simplification of the tools of analytical systems for "ordinary" users, popularization of voice control tools.

Advanced natural language analytics and processing

The most promising technological directions for the development of BI systems can be considered supplemented (expanded) analytics, as well as the processing of requests for data formed in natural language. These components are offered today not only by recognized leaders of the BI systems market, but also by many niche players. The use of these technologies will greatly speed up data analysis processes, bring BI functionality closer to the real needs of decision makers, and radically improve the quality of information and knowledge extracted from heterogeneous data sources.

In essence, advanced analytics includes artificial intelligence techniques and machine learning-based automation. BI tools using artificial intelligence can determine significant relationships between the main indicators and present analytical data in a simple and easy-to-perceive form, "explains Roman Dzvinko, Executive Director of the BusinessAutomation SPC.

Another interesting application of advanced analytics is the integration of analytics services with NLP tools - an area of digital assistants where employees can use voice commands to manage their business intelligence dashboard. The integration of analytical services with NLP tools is one of the important aspects of business analytics of the future, says Roman Dzvinko.

BI-systems are developing in the same way as the IT market as a whole, and analogies can be drawn with the introduction of search engines at one time, "says Artem Grishkovsky, commercial director of Triaflai (Trusted Environment, part of the Group of company Systematica). - To convert linguistic constructs into computer queries and vice versa, developments in the field of artificial intelligence are used, which is specially trained to implement a dialogue with a natural language system.

Not all managers have the opportunity to independently (and not with the involvement of an analyst) make a request for data, which greatly limits the penetration of BI systems into the business. A virtual analyst allows you to solve this problem: a person simply asks a question in the messenger and immediately receives an answer.

This works today, and tomorrow will free analysts from routine tasks, just as the invention of OLAP unloaded IT specialists from manually building reporting, "says Ivan Vakhmyanin, CEO and co-founder of Visiology.

The rebirth of CDC (Change Data Capture) technology

CDC (Change Data Capture) technology monitors changes in sources, which allows you to synchronize information between sources and data marts in real time. The CDC has been around for a CDC time. However, today she is going through a second birth.

We see the interest from customers and the emergence of new implementations of this technology among different vendors, "says Dmitry Savvin, architect of BI-solutions of Qlev Solutions. - Previously, for most analytical problems, the traditional approach was enough, when data was loaded and transformed sequentially, and indicators were transferred from model to model. Such a process, it is called ETL, made it possible, for example, to get a ready-made indicator of several thousand cash registers in 20 minutes. But that's not enough now. Customers now have more data sources to connect to the analytics system. The amount of data in these sources has grown, and the quality has fallen. At the same time, the business needs ready-made information without delay - in a mode close to real time. The application of CDC helps to solve such a problem.

Another reason for interest in CDC is the rapid spread of multi-cloud data processing architecture. This architecture assumes that the data is stored and processed in different places, which requires their quick synchronization.

Streaming analytics

The proliferation of 5G technologies, as a result - a new impetus for the development of the "Internet of Things" and "artificial intelligence" - will require tools to support real-time data processing and analysis.

Streaming analytics will become one of the main trends in the data management systems market, - predicts Alexey Vyskrebentsev, head of the Forsyth solution expertise center.

2017-2018

Advanced Analytics

Enterprises and government agencies have accumulated large amounts of information, the frequency of data updates has increased (they are generated almost every minute), while in a variety of formats: text, video and audio. Just accumulating data is impractical. Everyone wants to benefit, monetize them, increase operational efficiency. The issues of "traditional" BI have already been resolved for many.

For this reason, the demand for predictive and advanced analytics tools will continue to grow. For example, for systems that directly increase the operational efficiency of companies: optimizing logistics, managing inventory, building dynamic pricing models, creating individual promotional offers, and so on, "says Yulia Kudryavtseva, director of strategic development at Forsyth.

Timur Akhmerov, General Director of BARS Group, has a similar opinion. In his opinion, it is no longer enough to use only "classic" BI technologies.

The data is growing exponentially. Many companies already have their own Big data, work with which requires the use of advanced analytics using machine learning, neural networks, Data Mining. The domestic market is ripe for data analytics, which will allow building hypotheses and forecasts, he is sure.

Big data on their impact and significance are compared to natural resources and minerals. Like minerals, they first need to be mined, cleaned and processed, so that they can then become gilded. Companies, regardless of their size, do not just want to analyze and visualize their data, they need to get a forecast and find out the correlation with various influence factors in the context of territory, demography, season and other environmental characteristics.

The purpose of the implementation of analytics is to make an informed decision on which areas to stimulate and where to invest for the greatest return and profit, think about counter actions, neutralize negative factors of influence or change priorities. In this regard, we see the development of new professions and a shortage of personnel in the field of Data Science, predictive modeling, artificial intelligence and machine learning, "says Denis Seroshtanov, head of information and analytical systems at Interprocom.

Yuri Vostrikov, commercial director of Norbit (part of the Lanit group of companies), also records the transition to building predictive models, to trend analysis, predictive analytics from deep work with data and research on this data.

The trend will continue in the coming years. Any business associated with a mass client is now interested in automating research processes and studying its audience, the automatic formation of Next Best Offer, built on the analysis of a huge amount of data online, he believes.

Self-Service BI

If earlier BI tools were used primarily for creating regulatory reporting or tasks for visualizing and building dashboards, then the last years are the years of Self-Service BI.

Business users have already increased certain competencies, which allows them to independently analyze data, which makes those BI tools that allow implementing such Self-Service scenarios more in demand, "says Andrey Baibutov, Business Development Director of the BI Department of Korus Consulting Group.

Denis Seroshtanov from Interprocom notes a similar trend. According to him, ordinary business users are striving to be more and more advanced in working with big data in order to remain competitive in the labor market and in their company. And manufacturers of BI systems are increasing the volume of functions and integrating more and more simple analytical tools into their applications, providing them with short video courses, thanks to which users can quickly master and quickly use new tools in practice.

Such, I would say, an agile approach and self-services are most often practiced in the segment of small and medium-sized businesses, he said.

Import substitution

Another trend is due to import substitution. State and near-state companies are looking for domestic or open source solutions.

This is a fairly open market, since there are practically no high-quality and mature systems from the point of view of, for example, Self-Service BI, "says Andrey Baibutov.

Yuri Vostrikov from Norbit talks about replacing expensive analytical CRMs with more affordable predictive analytics tools.

There are already domestic vendors on the Russian market who have chosen the direction of BI solutions as one of the foci of development, he recalls.

Open Source

For economic, political, and other reasons, many companies choose open source solutions.

According to Georgy Shatirov, director of the Technoserv big data competence center, classic BI solutions today give way to fast open source modules with the ability to customize all system elements for themselves. More and more corporate clients of the LA (large accounts )/SME (small & medium-sized enterprises) segment rely on open source when forming the architecture of corporate reporting systems.

Commercial organizations choose flexibility and non-proprietary solutions. In 2019, this trend will intensify thanks to the dynamically developing community of developers of open source solutions and their effective model for the development of IT systems, - Georgy Shatirov is sure.

Clouds

An important trend in recent years is the use of cloud solutions. Despite the fact that certain applications deployed in the clouds are already present on the Russian market, for data analysis tools this is primarily an on-premium story: the customer deploys the platform in its own IT infrastructure and conducts development on its own or with the involvement of a contractor.

The Russian market has only recently begun to look at practices actively promoted in the Western market by companies such as Amazon, Google and others, which have all the necessary architecture and business applications, including BI and Big Data, deployed in the cloud. Users have the set of tools they need to work or some interfaces for working with data. There are different mechanisms for business models of such interaction, most often a payment scheme for used resources is used with one or another user's request, "says Andrey Baibutov from Korus Consulting Group of Companies.

Roman Konovalov, CEO of ID Management Technology, adds that thanks to the transition to clouds, which has simplified and reduced the cost of installing, maintaining and scaling the analytical infrastructure, even the SMB sector can experiment with advanced solutions in the field of data processing.

Cloud computing technologies allow you to "test" any latest solution, up to artificial intelligence technologies, on one or more departments of the company - and already, depending on the effectiveness of the pilot, decide on a full-scale implementation, he notes.

BI capacity growth

Another large-scale trend is the multifunctionality and growth of the power of BI systems, the transition to streaming analytics, the use of machine learning technologies and artificial intelligence. The modern business intelligence system should provide quick access to reliable data, external content, and be compatible with trialware.

All this is handled by "Forsyth. Analytical Platform. " It implements decision support functionality, including predictive analytics (time series forecasting, scenario modeling and optimization tools), data mining and machine learning tools, Data Governance, Visual Data Discovery, as well as ready-made connectors to Big Data class systems, structured and unstructured sources, - said Yulia Kudryavtseva, director of strategic development at Forsyth.

According to Georgy Shatirov from Technoserv, Big Data and ML (machine learning) have finally become commodity class technologies. Being the basis for business development, they should be present in each company, he is sure.

Other trends

Among other trends, the desire for ease of work with analytical complexes should be noted. Fully functional BI systems are easier for business users to understand and understand.

Mobile analytics is also developing. Mobile solutions are becoming more and more in demand, and their implementation is expanding. Scenarios such as a mobile voice assistant asking a question directly to the BI system, by analogy with Siri or Alice, are also possible here, says Yulia Kudryavtseva.

In addition, modern BI solutions introduce gamification elements into the data analysis process, which significantly improves the perception of information and reduces the time to make a decision.

The demand for real-time analytics systems is growing, the use of which allows the business to interact more efficiently and quickly with the client.

There has also been a steady trend towards BI monetization. According to Dmitry Kulagin, Head of BI of Jet Infosystems, companies are beginning to receive real financial benefits from the accumulated data, for example, from the use of focused marketing campaigns or from providing access to the analysis results.

More companies are preparing or already hiring Chief Data Officer (CDO) - about 15% of respondents have already implemented this position in their companies, according to a global study by Dresner Advisory Services.

It is CDO that is responsible for the management and use of corporate data - it makes information a working and extremely important asset, - notes Roman Konovalov.

A wide list of trends is voiced by Yuri Efarov, CEO of Sapiens solutions:

• Against the background of the high cost of storing data in the systems of first-line vendors, customers are striving to reduce the cost of storing data, especially in the future, when it comes to a significant increase in data in the next 2-3 years.
• The desire of customers to be able not only to process large amounts of data, but also to do it "quickly," as well as the desire to have "operational-configurable" systems for a changing process and new business requirements. In the limit, the business user himself would like to make changes to the process.
• Customers' desire to have interactive panels (dashboards) while maintaining the ability to work flexibly with analytics (add, remove analytics, change indicator definitions).
• "Analysts" want to get the data "in the basket" (according to the principle of "data supermarket") and then perform their analytical processing on the data "from the basket."
• The desire of customers to build an enterprise data model (the entire company) in the paradigm: managing data from sources and bringing it to the corporate model, managing the data lifecycle (accounting "aging, etc.)
• The desire of customers to build microservices and micro-applications on the corporate data model instead of the previously dominant "monolithic" applications.
• Building process applications over BI systems.
• Market-leading companies have assembled large in-house teams of business analysts and developers. These teams solve many tasks on their own without involving external contractors-integrators.

According to Sergey Tsurukalov, Head of BI Practice at BI Partner (I-Teco Group of Companies), the general trend is to move away from traditional BI platforms of corporate scale. They will continue to carry the function of reporting systems in enterprises, together with corporate repositories, becoming one of the key components in the IT infrastructure, but overly heavy in the modern world.

If you turn to the experience of a decade ago, all the work was carried out using the classic approach to project management. For many reasons, Agile is becoming more relevant today, and a new generation system is more convenient and simpler to work in this mode, "notes Tsurukalov.

2015-2016

Increase in the share of domestic solutions

The main consumers of BI systems are still highly competitive industries - retail, telecom, banks, production. These are mainly projects implemented using software products from Western vendors. However , the import substitution process is becoming more and more noticeable.

Today, a significant share of IT budgets is formed by state-owned enterprises and organizations with state participation. For them, the purchase of foreign software is impossible at the legislative level, - said Roman Baranov, head of business analytics and data storage at CROC.

At the same time, import substitution is not the only argument in favor of domestic products.

Prices for foreign solutions, taking into account the current course, are simply unbearable for many companies. And if at the end of 2015 the domestic software on the BI market was about 10-20%, then by the end of 2016 its share will become much larger, - Roman Baranov is sure.

Andrey Baibutov, Business Development Director of the BI Department of Korus Consulting Group, also notes a significant increase in the share of domestic solutions in the BI market. According to him, this is mainly due to the public sector and the financial services industry.

I think this trend will continue. Over the past two to three years, commercial companies have well realized that most of the costs are licenses and support for Western software, so it is often more profitable for them to develop and maintain their own product or purchase a new one in the domestic market, which at the total cost of ownership will be much cheaper than its Western counterpart, Baibutov said.

Ivan Vakhmyanin, CEO of Visiology, also says that the share of Russian software in the market is growing. In his opinion, domestic BI-solutions save the budget of the licensed component of the project and use the released funds for consulting, implementation or other projects.

At the same time, Evgeny Kurilovich, director of the analytical technologies department, Force, adds that there are not many domestic fully functional analytical platforms on the market that can compete in their capabilities, performance and reliability with foreign counterparts. "And we do not see new powerful solutions for Russian developers in the field of BI," the expert concludes.

Developing Open Source BI Tools

Another important factor for the development of the market is a serious decrease in the cost of implementing BI solutions, primarily due to the development of Open Source tools.

If earlier the deployment of a BI system, its integration into the existing infrastructure for data collection and configuration took months and years, now it is possible to collect and visualize clearly marked KPIs in a matter of weeks using free software, says Pavel Adylin, executive director of Artezio.

The most in demand, according to him, are such Open Source tools and Community versions of commercial software as Pentaho, Jasper and BIRT.

Konstantin Chernousov, Deputy General Director of Vesolv, adds that the reason for the growth in demand for open source technology is a decrease in IT budgets.

Medium business interest in "light" BI systems

Another qualitative change is noticeable in the market - this is a reorientation of demand. If earlier the implementation of BI systems was the prerogative of large business and government agencies, at the moment medium-sized businesses have also begun to play a significant role in this market.

According to Pavel Adylin, Executive Director of Artezio (Artesio) (part of the LANIT group of companies), the main reason for this change lies in the new economic conditions, in which tools for improving business efficiency become an integral part of the management strategy. In addition, BI tools have ceased to be for business only a means to increase transparency of activities.

Enterprises have learned to distinguish quantitative and qualitative characteristics of activities based on the available data. As a result, the demand for the introduction of "light" BI systems that solve highly specialized tasks of monitoring specific indicators has seriously increased, Adylin notes.

A similar trend, speaking of the growing interest of medium-sized businesses in BI, notes Yuri Vostrikov, deputy commercial director of Norbit.

In our practice, we are increasingly seeing a preponderance of customer interest from heavy BI platforms (such as Cognos or BOBJ) towards lighter platforms such as Qlik, for example. Easy from the point of view of the cost of implementation, and from the point of view of the time from the start of the project to the commissioning, i.e. in essence, the receipt of the first real results by the customer.

Evgeny Smirnov, Deputy General Director of Navicon, speaks of an increase in the segment of so-called self-service systems that do not require special knowledge from the user or support of the IT department.

If earlier, according to him, most of the technical tasks for business analysis (primarily data warehouse design) fell on the shoulders of the IT department, today tools are popular that allow an ordinary business user to conduct their own data research, and with minimal labor.

For example, Microsoft Power BI or IBM Planning Analytics cloud tools provide full-fledged data collection and processing capabilities, as well as an interactive dashboard for visualizing reporting ("dashboard").

For business, this means that most of the processing tasks go directly to the divisions of the company. On average, the cost of self-service data processing and reporting visualization tools is growing 2.5 faster than traditional BI tools, the Navicon representative notes.

BI in the cloud

Maria Venediktova, vice president of GMCS, believes that the interest of the middle market in business intelligence systems has largely become possible due to the reduction in the cost of BI solutions, most of which are now available in the subscription cloud.

The savings on capital investments that clouds carry today have already been estimated in the West and are beckoning our financiers, adds Vladimir Sizykh, RDTECH Marketing Director.

However, if the analytical system is already implemented in the company, the customer is in no hurry to transfer it to the cloud.

I would also like to note the fact that many major world vendors are trying to transfer customers to their "clouds." This is a profitable business for the manufacturer, but the meaning is not very clear for the customer, and while he is in no hurry to send his serviceable analytical infrastructure to heaven, "notes Andrey Tiunov, General Director of BI Partner (I-Teco Group of Companies).

In addition, this process is hampered by the imperfection of the legislative framework and the distrust of companies in external storage.

Demand among government agencies

An increase in demand for BI class systems is noted among government agencies. A number of experts record and predict an increase in the number of such requests.

Konstantin Chernousov, Deputy General Director of Vesolv, says that interest in BI, in comparison with other areas, is growing, and more and more requests come from the public sector than from the commercial one.

That is, when deciding what technologies need to be implemented, the head of the enterprise gives preference to BI-technologies necessary to improve management efficiency, "adds Chernousov.

Evgeny Smirnov from Navicon believes that government agencies and various near-state structures will play a significant role in the BI market in the near future, from lawmaking and regulation to state orders.

In addition, according to the expert, BI technologies enriched with the approaches of machine learning, big data analysis and artificial intelligence receive support and development at the state level.

It is becoming important for the state that the development of BI technologies, the Internet of Things and other analytical tools will reduce the costs of industrial enterprises and the economy as a whole. Already, within the framework of the National Project program, experts are working to create industry databases for the Industrial Internet of Things. Initiatives to create professional associations are being developed: Rostelecom in April initiated the creation of a consortium of the Industrial Internet and proposed to assume the duties of the IIoT infrastructure operator in Russia. There is a special association in Russia - Tizen, which unites many technology companies to develop a domestic safe and open platform for the Internet of Things and "smart" infrastructure of enterprises in all industries, from healthcare to industry, says Smirnov.

New players

New players are entering the BI solutions market, those who have historically been able to accumulate and continue to consolidate large arrays of diverse data. First of all, this applies to companies such as Yandex and Мэйл.ру, as well as telecom operators. They assessed the prospect - and began to develop their own analytical tools, processing their information bases.

Evgeny Smirnov, Deputy General Director of Navicon, cites Yandex Data Factory as an example, which has developed algorithms for solving its own problems within the framework of Yandex's search and advertising business, providing free services to search engine users (targeting ads, predicting traffic jams, etc.).

But algorithms analyzing the "relationships" between the data, according to the company itself, are already actively working in the b2b market: from analyzing traffic congestion for logistics companies to monitoring industrial production capacities, says Smirnov.

In particular, according to him, the Magnitogorsk Metallurgical Plant (MMK) has already implemented several stages of a joint project with a recommendation service from Yandex Data Factory to optimize steel production by saving the enterprise on ferroalloys. After the implementation of the solution based on machine learning and Big Data, the plant will save up to 23 million rubles a month. According to the management of the plant, the pilot project - optimizing warehouses and moving coal mines - paid off in 6 days.

Other trends

Participants in the domestic BI market name many trends that they face, and which in their opinion prevail in the market.

Thus, Ivan Vakhmyanin, CEO of Visiology, considers raising maturity as the main trend. According to him, today companies already understand well that BI is not a magic button, but a whole set of methods and tools that need to be competently implemented. At the same time, the benefits of BI implementation are obvious in any industry.

It also fixes the tendency to increase the duration of projects. This is due to the fact that many companies have tightened their budget policy, so BI implementation takes place only the next year after the pilot project and the decision on implementation.

Maria Venediktova, vice president of Maykor-GMCS, speaking about market trends recalls Gartner's forecast, according to which by 2019, 90% of large companies will be responsible for data management by Chief Data Officer, data director. It will identify threats to the external and internal environment, identify and study trends, make strategic proposals that can be implemented in the company. The usual management decision-making schemes will change and will rely on analytical technologies.

Obviously, this will affect our country, - Venediktova is sure. - The opportunities to increase business value and build competitive advantage with data processing and analysis technologies are truly endless. Companies can develop the scenarios they need and put them into practice.

Andrey Tiunov, CEO of BI Partner, among the market trends highlights the growing interest in the data vault methodology used to organize corporate data warehouses.

In 2016, the experience of implementing "data sets" was indicated in the requirements of a number of large competitions, "Tiunov notes, adding that one of the Russian banks plans to start building a corporate storage according to a new methodology.

Evgeny Kurilovich, director of the analytical technologies department, Force, says that if earlier one of the main tasks of BI projects was to automate analytical reporting, today most clients are concerned about monetizing the data at their disposal when it comes to projects using Big Data technologies.

In the future, according to him, the trend will be a movement from traditional business analysis to data research.

This means that products will develop that allow you not only to perform queries and calculations, but also to examine external information that is not adapted for processing by means of relational technologies. We can expect the development of Data Discovery platforms and the increasing popularity of statistical and mathematical research and forecasting tools. This is by no means about replacing BI tools with something else. The new class of tasks does not cancel traditional analytics, but enriches it, expanding the usual boundaries, - notes Kurilovich.

Konstantin Chernousov, Deputy General Director of Vesolv, notes a change in the structure of demand. In his opinion, there is a growing need for non-classical BI solutions that have the ability to process large amounts of unstructured data, text analytics, data visualization and have a convenient graphical interface.

Data visualization examples from Visiology

Interactive visualization and non-standard widgets make visualization not only lively and interesting, but also allow you to show more information from different sides within one Dashboard. The figure below shows the Dashboard for the analysis of product categories.

Standard widgets, such as histogram, circular and others, do not always allow you to clearly display specific data, therefore, for example, for the analysis of seasonality and the distribution of indicators by day, week, month, work and weekend, Polymedia recommends using a heatmap and radial graph that best demonstrate the dynamics of changes and sales efficiency.

Evgeny Smirnov, Deputy General Director of Navicon, for his part, notes that with the growing trend towards digitization of any data, be it data from industrial sensors or car numbers recorded by video cameras, companies are increasingly having to work with unstructured data. In particular, the systems of video analytics, machine vision - solutions for recognizing numbers, samples, faces are being improved and are gaining popularity.

For example, there are already more than 50 thousand users around the popular global open source library Open Computer Vision. The volume of such data is growing annually, which affects the development of the BI market.

Vladimir Sizykh, Marketing Director of RDTECH, calls Big Data technologies an unambiguous trend in recent years. Moreover, in his opinion, this term today actually replaced the term BI, or rather even completely absorbed it.

If you look at the latest contests placed on trading platforms, you can see that solving published business problems requires a synergistic effect of connecting classic BI with Data Science and using Big Data technologies, Vladimir Sizykh says.

2012-2013

In 2011, experts said that the Russian market is changing the implementation paradigm - from simple analytical systems in favor of more complex and deep analysis systems. Partly in 2012, this forecast justified itself, but in 2012 the idea of ​ ​ the genius of everything simple again had a strong impact on the market in reborn quality: the development of mobile analytics systems and data discovery systems sharpened for end users became truly massive. The model of affordable analytics "in the pocket," the analysts of "several clicks" turned out to be so close to the business that more and more potential customers of BI systems make requests to integrators for the implementation of such solutions.

"Second wave" of BI implementations

See also: Estimates of the BI market in Russia

The peculiarity of the Russian BI implementation market is that units of companies introduce business analysis platforms in full functionality for absolutely all processes. On the contrary, the most common approach is when one company has several isolated business analysis systems, sometimes not even different platforms that cover different tasks within individual departments and departments. In banks, for example, the number of operating BI systems can reach 10-15 pieces. Moreover, such customers who have already evaluated the benefits of business analysis in practice do not stop there, initiating new and new implementations, which largely formed the basis of the "second wave" of BI implementations in 2011-2012.

At the end of 2012-2013, the "third wave" of BI implementations began to actively form, associated with the development of new approaches to data storage and analysis by Russian companies. Now in Russia, dozens of test implementations and pilots in the field of big data and computing in RAM have begun, many of which will go into the category of full-fledged implementations in 2013. From a technological point of view, the Russian BI market does not experience the slightest lag behind the world in terms of the availability of advanced technologies, but their development is just beginning.

BI to mass

See also:

• Self-Service BI
• What is data discovery?
• Mobile Analytics: Russian Realities

In 2013, the trend of "analytics for all" will take hold and in the future is able to make a small revolution in the business analysis market in Russia. If vendors are able to offer sufficiently developed and, most importantly, affordable analytical tools for business users, including mobile ones and those provided by the SaaS model, then an increasing number of companies will choose such BI tools to solve their daily business problems. It is in this market segment that a sufficient number of implementations can be expected in the next three years, so that by 2015 the Russian BI market will be able to finally reach maturity.

In fairness, it is worth noting that the vast majority of companies in the Russian market are still experiencing the stage of buying the first BI systems. However, over the next two to three years, the qualification of customers of BI solutions will grow rapidly, so that the intelligent tools of BI systems will become more in demand. But a large number of such projects in Russia are still very far away.

Olga Gorchinskaya, head of research projects and the Big Data direction of FORCE, notes that the demand for BI systems is growing more and more every year, and in companies in almost any industry. "

From just" rules of good tone, "projects for the implementation of BI-systems have turned into a clearly formed need in the market," she said.

Olga Gorchinskaya says that among the sectors, government agencies are becoming especially prominent players - FORCE has already completed several large projects to create data warehouses in large ministries and departments.

Andrey Rozanov, Head of BI at RDTECH, confirmed that the demand for analytics among representatives of medium-sized businesses is steadily growing. Although the average business looks at the introduction of serious analytical solutions with great skepticism, already now the undeniable fact is that small and medium-sized businesses refuse to solve the problems of analysis in Excel in favor of specialized analytical applications.

"Third Platform"

See also:

• Analytics Storage Systems
• Big Data (Big Data) Global Market
• Why do you need In-Memory DBMS?

information technology Analysts IDC have successfully characterized the critical mass of changes in the industry over the past few years by the transition to the "third platform." It is understood that the first computer platform has historically formed mainframes, the second - traditional computers of client-server architecture. The third platform is a combination of mobile, social and cloud technologies and that big data defines the paradigm for the further development of the entire ICT industry as a whole.

In the business analysis market, the impact of the third platform is already felt very strongly. The growth of the big data phenomenon and unstructured data has led to the development and development of new technologies for information processing and storage, including databases of the type Hadoop and processing in RAM (in-memory). As mentioned above, mobile tools BI are also actively developing, cloud BI solutions are waiting in the wings.

In Russia, system integrators note interest in in-memory data processing technologies (IBM Cognos TM1, QlikView) and specialized analytical DBMS (Oracle Essbase, Sybase IQ, Teradata, Greenplum, SAS ). This is in line with global trends in the BI market. Such solutions find their demand primarily among companies working with large amounts of data - finance, retail, telecom, and so on.

The most expensive part of the overall BI loop in the company is the data warehouse, so serious market growth is impossible without increasing demand for them. Probably, companies will strive to move to "operational analytics" or "data-driven processes," this will require new architectures in storage (previously this approach was implemented only by Internet companies), experts say.

Dashboards and Visualization

See also: Data visualization

Interactive analysis tools remain popular tools on the Russian market - ad hoc requests and information panels (dashboards). According to FORCE expert Olga Gorchinskaya, this means that customers are increasingly interested in the opportunity not only to see the report, but also to go online to detail, quickly get answers to new questions and thus understand the causes of problems and make timely management decisions. Other technologies that accompany almost any project include spatial analytics, which allows you to use geographic maps as an analysis tool, and "active" analytics that integrate business analysis with business processes.

In general, in the context of the movement of analytics "to the masses," visual means of presenting data play an increasing role in choosing a solution. Advanced data visualization tools have become an integral part of corporate BI platforms. Some vendors, such as Tableau, have made visualization the cornerstone of their analytical systems.

Predictive analysis and data mining

See also Predictive analytics (predictive, predictive, predictive) Predictive analytics

The most popular feature of BI systems was and remains data analysis. The basic features that are always relevant include OLAP, reporting, quick presentation of the necessary information in various slices, simplicity and clarity of the user interface. However, today's users often no longer have enough funds for the so-called traditional BI, and tools of advanced analytics are becoming more and more popular: modeling and forecasting the situation, optimization, and identifying dependencies.

According to market participants, interest in in-depth analytics - statistics and data mining - is becoming more noticeable. Despite the fact that it is too early to talk about the great demand for in-depth analytics, there are already examples of its successful implementation, and in the coming years the popularity of these funds will undoubtedly grow, Olga Gorchinskaya believes.

Demand for predictive analytics is growing from both government agencies and corporate clients. The use of analytical tools for forecasting and modeling the situation allows you to build complex models that take into account the internal and external environment of the organization, which significantly improves the quality of forecast estimates. This largely contributes to the development of services for the creation of so-called situation centers, in which BI forecasting and modeling systems become one of the main components.

As the BI systems accumulate sufficient amounts of data for full analysis over a long period of time, users will gradually move away from the set of reporting forms to the analysis of information. Data mining remains a promising direction.

Cloud and open source projects

See also:

• Cloud/SaaS BI: Perspectives
• Open Source BI

The Russian market BI- systems also follows global trends in the development of technologies cloud computing/. SaaS However, according to most experts surveyed by TAdviser, so far the demand for cloud BI is more in its infancy: so far there are Russia few such projects. If we talk about already implemented cloud BI projects, they, for the most part, have point functionality that is not comparable to a full-fledged BI project.

The same applies to BI open source with - for Russia this business model is still too complex. For 2010-2011, it is difficult to recall the more or less large implementation of Open Source BI in Russia. Experts believe that one of the reasons is the rather weak marketing worthy solutions of Open Source BI in the Russian market. SMB, as a potential consumer of open source BI solutions, knows a little about the advantages of Open Source BI, so it trusts commercial BI systems to a greater extent. Interestingly, some integrators are already working successfully with cloud BI, for example,. CROC

Development of domestic products

Despite the great popularity of BI Western vendors in Russia, the popularity of domestic products is also growing. This is not to say that competition in the market is so high that there are serious tensions between Western and domestic players, but, nevertheless, it is gratifying that domestic expertise in the field of business data analysis is growing. Suffice it to say that the Russian platform Forsyth. Analytical Platform (formerly Prognoz Platform) from Forecast for the second year in a row fell into the magic square of Gartner, which means recognition of the system's weight not only in the Russian but also in the international market.

In addition to the real sector, the Prognoz Platform is also actively used in the public sector. Strong local solutions are Deductor from Loginom Company (formerly BaseGroup Labs Analytical Technologies) and Intersoft Lab (Intersoft Lab): Contour from Intersoft Lab (Intersoft Lab). If Western platforms win in functionality, versatility, manufacturability and performance, then the solutions of Russian companies are faster to adapt to the customer's requirements, better support national standards. This is especially important for the public sector, where domestic analytical solutions are used more often. Commercial companies - banks, telecom, retail, prefer Western BI platforms, explained FORCE expert Olga Gorchinskaya.

New Directions of Analysis

Georgy Naneishvili, Development Director of the Qlik Partner Network, notes the growing interest in cost reduction solutions: now the business is interested not only in sales, but also in the cost structure, and is looking for ways to save money.

"And, paradoxically, I am ready to pay money for this," the expert notes.

Also, more and more companies are showing interest in solutions that can be quickly deployed and get immediate results: a dynamic competitive environment dictates requirements not just for the speed of projects, but for the speed of rebuilding models and solving problems. Qlik also notes an increase in interest in such an area of ​ ​ analysis as personnel analytics - companies are increasingly interested in employee performance, internal personnel reserves. Analytics not only from personnel systems and timesheets, but from accounting systems - to understand the employee's effectiveness - flock to the HR directors' panel; from the portals for hiring personnel - to see how competitive the salary of certain specialists is; from security systems - indicating visits to sites and the time spent on them or downloaded documents.

"Believe me, on the basis of this data, very interesting and important conclusions can be drawn for the company," Georgy explained.

See also

BI and Big Data Overview

Big Data - Catalog of systems and projects

Business Intelligence (Russian market)

Big Data (Russian market)

Big Data Specialist

Big Data

Business Intelligence (Global Market)

Geography of BI projects

Russian BI: Industry Specific

BI Implementations in Russia - Typical Errors

How Business Intelligence technologies evolve and become available to everyone