Data management

Data management - A process related to the accumulation, organization, storage, updating, storage, and retrieval of information.

Data management includes

• Data Analysis
• Data Modeling
• Database Management
• Working with Data Warehouses
• Retrieve, convert, and load data
• Data mining
• Data Quality Assurance
• Data Protection
• Data Encryption
• Metadata Management (Data Repositories)
• Data Architecture

A separate TAdviser article is devoted to the very concept of "Data."

Separation of functions between Data Governance and Data Management

Just as the auditor controls the financial processes but does not actually manage the financial, data management ensures proper data management without directly managing the data.

Data management is an inherent division of responsibilities between oversight and execution

2020: Aruba: Organizations in Europe, Middle East and Africa do not have enough tools to work with data

On May 21, 2020, it became known that according to a report by Aruba, Hewlett Packard Enterprise, organizations face the problem of benefiting from data, as systems are rebooted due to the growing number of requests.

Based on a survey of more than 170 opinion leaders in IT and network engineers in the Aruba ecosystem of EMEA, the report reported that most respondents were disappointed with the deficiencies in data management. According to the survey, 61% of respondents "do not fully control the data of their company," 51% - "cannot consider the data holistically," and 52% - "cannot extract useful information from the data received."

The Data to Decisions: A Rulebook to Unlock the Power of your Data report describes six steps to help organizations better manage their data. Key report topics:

• Respondents confirm that the potential of data allows you to use it for more efficient and customer-oriented work. The biggest benefits of data management are the ability to provide customers with better services (60%), increased efficiency (38%) and the introduction of production innovations (35%).

However, respondents also identified deficiencies in existing systems and infrastructure that may limit these opportunities. When asked how they would like to use data that cannot be used as of May 2020, respondents answered that their priority is to increase the level of security (63%), introduce more analytics in real time (55%), make more informed decisions based on data (55%), and more effectively use data to fulfill the main tasks of the business (45%).

• For May 2020, another serious reason for concern is the lack of relevant skills and knowledge among company employees. More than a third (36%) of respondents said that "lack of skills to manage rapidly growing data" is one of the main problems for them. At the same time, the biggest fear among respondents (28%) is that "employees will not agree with data management policies."

In order to improve the skills and knowledge base of data management, organizations should focus on developing the skills of staff with deep industry knowledge, hiring a Director of Data Processing and Analysis (Chief Data Officer), and create data management teams that include decision makers for all key business tasks to ensure that their business and data management strategy needs are reflected.

Companies already have most of the most valuable knowledge. Training employees to communicate with information technology experts and use APIs is often much more valuable than asking technical science candidates to quickly understand the industry. narrated by Tom Chatfield, author of the report and technical analyst

• In addition to the fact that as of May 2020, data security is at the top of the list of priorities of IT specialists, it also causes them the greatest fears. Two of the three biggest problems related to security or compliance with company requirements and policies: 21% of respondents fear hacker attacks, and 12% that their organization will be fined in accordance with the European Regulation on the Protection of Personal Data (GDPR).

The report contains a number of recommendations to improve security, such as classifying data according to different levels of risk, developing a plan of action for data breaches, and training staff through practical scenarios to raise awareness of threats.

Employees are the last line of security. You can use the best firewalls and - VPN resolutions. But if anyone keeps file it on passwords their mailbox, and they Gmail crack it, then everything goes out of control. noted Andrew Grill, author of the report, futurist

Each organization understands what opportunities data provides to innovate, develop products, and improve customer service. As data and solutions move to the edge of the network, companies need to be confident that their systems and processes will cope. As stated in this study, organizations need to improve the skills and training of their employees, create effective management structures and pay special attention to data security. In a pandemic, these recommendations are even more relevant, as work at home becomes the norm, and home Wi-Fi does not meet key security requirements, while the number of targeted cyber attacks is growing. concluded Morten Illum, Vice President of Aruba in EMEA

2019: Key issues and errors in data management

The relevance of Data Governance is growing every year. Indeed, the need to organize processes aimed at improving the efficiency of data collection, processing, storage and use as a valuable asset is already obvious to almost all companies. A lot is said about the advantages that companies bring to properly built data management processes, and many organizations have already begun to implement this initiative. At the same time, organizations often make similar errors that negatively affect the pace of implementation and the effectiveness of the created data management processes. About what mistakes these are, how to avoid them, and what questions the organization should find answers to during the Data Governance implementation process, [http://www.tadviser.ru/a/498875 in the material prepared for TAdviser, says Svetlana Bova, Chief Data Officer of VTB Bank].

2016: Efficient data management increases sales by 3 times

According to Experian research, in which 1,400 organizations from eight countries took part, companies are increasingly aware of the economic potential of information: according to 79% of respondents, by the end of the decade, customer data will determine most of the sales decisions. However, almost all respondents - 90% - still believe that they lack a constructive approach to effective data management.

On average, almost 25% of customer data contains inaccuracies. Among the most common errors:

• incomplete or missing data
• out-of-date information
• data duplication
• conflicting information

According to an Experimian study, companies believe that they could increase sales by almost 29% if accurate client data are available.

It is estimated that in 2012, an impressive amount of data - 2.5 quintillions of bytes - was generated every day - at a time when mobile communications were estimated to reach 61% of the world's population. Assuming that by 2017 this figure will increase to 70%, it becomes obvious that the volume of data in the coming years will grow exponentially.

Such "explosive" data growth is a challenge for companies. As 84% of respondents noted, their organization currently considers the data an integral component of the business strategy. In this regard, 82% of companies in the next five years plan to hire data specialists. As the previous Experimian study found, today the importance of the data director (CDO) is growing, which develops work with data as part of the company's strategic activities, ensuring improved financial results.

Data management is also complicated by growing amounts of information and changes in the use of communication channels. According to 39% of respondents (compared to 10% last year), their organization has 50 or more contact bases. In addition, the use of social networks over the past 12 months has increased by 81%.

75% of respondents this year during the Experian study named e-mail as the communication channel most widely used for marketing purposes. At the same time, 73% of this group can give an example of the negative impact of inaccurate data on the business. Poor electronic address data not only leads to lower revenue, but also business problems such as poor customer service, inability to communicate with subscribers and useless costs.

97% of organizations strive to see the client as a whole, so effective use of data comes to the forefront, allowing each client to be considered as a separate person, with their own individual characteristics, and to develop commercial proposals taking into account the special needs of each such client.

The advantages associated with this holistic understanding of the client were cited as the growth of loyalty, increased sales and the possibility of strategic decision-making. Therefore, commercial companies recognize the importance of accurate customer knowledge and its impact on the financial results of the organization.

2013: Specifics of financial institutions

In December 2013, Qlik (QlikTech) released the results of a study that showed that despite the fact that after the global financial crisis, data management became especially important, more than two thirds (63%) of financial executives do not consider it necessary to consider this issue at the level of senior management.

According to a study conducted for QlikTech by Lepus, a third (31%) of financial institutions did not allocate roles and responsibilities in the field of data management, despite the fact that many factors in the business indicate the need to manage data in the financial sector.

In addition to the unprecedented increase in daily data processing, many regulations related to data management have been introduced - such as the Sarbanes-Oxley Act, US Securities Commission Rule 17a-4, Basel III and Solvency II standards, as well as the principles of the Basel Committee on Banking Supervision BCBS 239 (aggregation of risk data). In response, financial institutions had to develop common approaches to data architecture and modelling; solving this problem and provides data management.

The study focused on data management programmes in, and banks Europe North America countries in the Asia-Pacific region. It showed the need to consider these issues and take responsibility for them at the senior management level in order to ensure that data management infrastructures meet business goals.

This is all the more important given that the study has identified many business factors that contribute to the implementation of data management programs, as well as a number of critical functions in the management structure. The existence of such a business factor as the need to ensure regulatory compliance and reduce legal risks was recognized by 94% of bank executives. Institutional coherence (88 per cent) and greater openness and transparency of financial data and information (63 per cent) were identified as the next most important.

However, the main function of the data management infrastructure for the different banks participating in the study varies significantly. 44% of respondents called risk reduction one of the two main functions, and the other - the realization of business benefits, but only 13% consider compliance to be the primary function of the data management infrastructure.

Paul Van Siclen, Director, Financial Services Market Development, QlikTech, noted that since the global financial crisis, data management has become even more important as financial institutions have had to conduct a comprehensive analysis of their data strategies. "But in the absence of agreed goals and without considering these issues at the level of senior management, banks are unlikely to achieve the desired result," he believes.

How to use analytics to develop quality IT services

White Paper: Using Analytics to Develop IT Services

Loss of organizations from IT downtime and failures

Main article: Loss of organizations from IT system downtime and failures

Data Management

• Master Data Management System and Project Catalog
• Regulatory reference information management systems in Russia.
  Leading players and top trends

• Data management
• Chief Data Officer (CDO)
• Data Science
• Data scientist
• Chief Digital Officer, CDO
• Chief Digital Officer (CDO) in Russia
• CIO (Chief Information Officer)
• Chief information security officer (CISO)
• CFO - Chief Financial Officer
• System Administrator
• DataOps (data operations, data pipeline)

• Big Data
• Big Data in Russia
• Big Data Global Market
• Big Data Specialist
• Data Mining