Chief Data Officer, CDO

Data Office Functions

Data professionals are driving innovation and differentiation, revolutionizing existing business models, improving company communication with target audiences, and unlocking new opportunities to improve business efficiency.

The desire to increase the efficiency of the use of information resources will lead to a sharp increase in the number of companies with the post of data director (CDO) in the staffing table, analysts say. Gartner However, only half of them will succeed in solving their tasks by the end of 2019. The data directors will have to create a strategy that identifies indicators that link their activities to measurable business results.

A combination of high expectations and low awareness of data management technologies can make it difficult for data directors to get budgets and provide support to business users, which is necessary for the success of projects, analysts say. Many directors are already reporting conflicts with the IT service over the control of information resources. But successful data directors manage to establish contact with IT directors, overcome resistance and lead reforms. Analysts recommend explaining the role of data and information in business to company executives. In addition, it is recommended to highlight a basic level of data monetization and information management against which progress can be measured.

Key factors affecting the role of data director in the company:

1. Data Director Qualification

Data directors should be innovators and advocates who can make changes at all levels of the organization, prioritizing data management. 94% of respondents do not consider technical skills significant, directors according to the data are attracted from different positions in the industry, but an inspiring leader should have successful leadership experience at the highest level and an entrepreneurial vein.

2. Technology

Continually evolving technologies and continuous data growth redefine architecture responsibility and make data more relevant. The introduction of cloud solutions has shifted the focus from IT to data migration and change management. Therefore, organizations are increasingly focusing on data accuracy, which is becoming a top priority.

3. Transition to Digital Form

The growth of digital technologies entails differentiation and innovation, which force organizations to look for new business models and sources of income. This digital transition requires the leader to manage the data and comprehensively understand its capabilities. CDOs must transform data into business value and integrate it into the organization structure.

4. Regulatory and management

Data directors must adequately address the ethical issues that accompany the processing, use and application of data.

Algorithm for CDO Service Generation

Currently, there is no single correct algorithm for forming the CDO service. Its structure and influence largely depend on how it is used to develop the enterprise. The researchers of the analytical company Gartner, systematizing information by industry, came to the conclusion that whatever the positioning of the information director department in the management structure, the principles of organizing the CDO service structure are in any case divided into four main components^[1].

Organization of the company's information department on the principle of "machine room" (CDO Organization as an Engine Room): the CDO service ensures the company's operational data turnover, focusing on internal consumers. The list of tasks includes monitoring of any actions with data, as well as full control over the use of information assets, management and analytics of information flows of the company.

Everyone's CDO Organization: The main role of the information department is also to work with the demands of the company's staff, and at the same time, a certain emphasis is shifted to information assets energetically used by business leaders and individual specialists outside the traditional business framework. The mission of the information office is also to transform and introduce new digital business models throughout the company.

Information Department as a Business Provider (CDO Organization as a Business Service Provider) - The Enterprise Information Service provides operational data turnover for both internal and external users. The activities of the information department are extended to all distributed information assets of the company, while the information department itself is closely integrated into the company as one of the businesses.

Information Department as a Separate Business (CDO Organization Is the Business): information is one of the products offered by the company or is not separate from the company's product line. The information service in such an organization represents all services for servicing external and internal information flows that ensure the transformation and differentiation of the company's business.

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Data Governance Organizational Structure

Data Governance components include:

• Data quality management system with management and monitoring of business rules;
• Metadata management system: catalogue of available sources, tables, displays, data models and reports, history of data origin;
• Business Glossary - a managed catalog of business terms used in reporting and analytics;
• User portal by data: searching for data objects, owners, roles, datasets, viewing current chains of origin and rules on data quality, etc.

Prepared and provided by DIS Group

Data Governance - a discipline (methodology) for creating repeatable and scalable data management policies, processes and standards for efficient use of data or the process of creating reliable data across the organization, and keeping data reliable.

Prepared and provided by DIS Group

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

Operational Data Management Process

Courtesy of DIS Group

Data Discovery Data ^[1]

• Business Analysis
• Solution design
• Inventory of data
• Development of roadmap
• Planning changes (appointment date of stewards)
• Search/create/acquire data
• Data profiling

Monitoring and measurement

• Proactive monitoring
• Governance dashboards
• Process and data analysis
• Reporting, including reporting for compliance and risk reporting
• Asset liquidity management (business value, TCO, ROA)

Data Integration

• Maintaining a business glossary
• Data classifier and data links
• Enterprise IT Architecture
• Data Architecture
• Master data maintenance
• Define/adjust Data Governance policies, processes, rules
• Process data integration
• Definition of points and measured control rules

Using Data

• Data Quality Management
• Master Data Management
• Data Lifecycle Management
• Data Protection Management
• Data Availability Management

Data scientist

Main article - here

Data Specialist Errors

Companies seeking competitive advantage, customer knowledge, and development trends are expanding the use of data for decision-making. A good data specialist is invaluable for a company that is somehow represented on the Internet. It can process complex information and create machine learning algorithms ^[2]

The volume of data is growing, along with the number of skills and efforts required to implement data-driven initiatives. Mistakes can have serious consequences. Tools change and errors remain the same. The following are recommendations that will allow them to be identified and avoided. 1. Lack of programming knowledge "'

It's amazing how many people think data science has nothing to do with programming. The basis of data science was and remains the construction of a model using a long script. The quality of the script determines everything from scalability to model reliability when it begins to be used for production purposes.

An excellent data specialist should be a good programmer. I adhere to this rule: a senior data specialist must have programming skills at the level of an average software engineer, and a data specialist at the level of a junior software engineer.

2. Lack of defensive thinking

In this case, the saying "the best attack is good defense" is appropriate. Data experts should wonder: how erroneous can a model be at worst?

The only mistake can have severe financial and legal consequences for the company. If you do not check and recheck the code, guided by defensive thinking, there will definitely be mistakes in it.

Machine learning uses performance indicators such as accuracy, standard deviation, and mean absolute error. These are averages that do not replace defensive testing.

3. Non-productive use of time spent on data cleanup

It is not uncommon for specialists to spend weeks reviewing data, instead of moving to the creation of machine learning software. Too much time is spent cleaning up the data. The task of creating an end-to-end data stream is ignored. This is typical for data specialists who are physicists by education, unlike those who studied computer science.

Many project managers do not pay enough attention to the elimination of numerous errors, since by a certain date they must show the company's management the result of the work.

4. Waste of time studying individual models

If you study individual models for too long, you can lose sight of how these models should interact. Dynamic pricing may well affect the determination of prices for advertising. This question, of course, belongs to the competence of senior data specialists and their managers.

Actions must be taken on data collections. A data specialist can help his company go through digital transformation by organizing monitoring, testing and powerful analytics, creating a machine learning infrastructure. This will improve business management and solve problems. They should be encouraged to do so.

2020: Svetlana Bova, Chief Data Officer of VTB Bank - on the main issues and errors in data management

The relevance of the management theme data () Data Governance is growing every year. Indeed, the need to organize processes aimed at improving the efficiency of data collection, processing, storages 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 implementation of Data Governance, in material prepared for TAdviser, says Svetlana Bova Chief Data Officer. bank VTB

2016: Directors are promised rapid and rapid career growth

According to the forecast of Gartner analysts, by 2020, 15% of the directors according to the data (Chief Data Officers - CDO) expect great prospects. They will eventually take the position of top managers - marketing directors, operating or CEO. As the authors of the study explain, organizations that decided to introduce the CDO position into their staff are aimed at maximizing profit from it. 30% of the total number of surveyed directors according to the data replied that they report directly to the general director of the company. According to the management of such enterprises, CDO specialists strengthen the company's competitiveness by helping in strategic planning and making important decisions, as well as leading ^[3] digital business processes^[4].

CDO is an operational unit with qualified staff, with a budget and responsibility. In 54% of the organizations we surveyed, they said that such a department was formed in their entirety or in part. Another 20% are studying the issue or plan to create a department next year. And only 19% of respondents are not yet ready to take up such a division, "said Gartner Vice President Debra Logan.

The main tasks of the CDO department were to increase the level of customer confidence (62%), increase competitive advantages (60%) and increase the efficiency of the enterprise (54%). 69% of survey participants believe that the main task of data directors should be analytics initiatives, 68% - that CDOs should manage data in the enterprise. Another 64% of respondents believe that the responsibilities of CDO should include developing strategic tasks in the company and ensuring the information stability of the enterprise.

Big data experts ready to lead changes in companies

As the use of data and analytics in companies continues to grow, businesses that ignore CDO support will face crises. "27% of respondents pointed to the threats of analytics and data crises as the reason for the creation of data management departments or a staffing unit. 24% of respondents said they went for it by order of the board of directors. Another 41% - by order of the CEO or CFO, "said Gartner Vice President Jamie Popkin.

Analysts explained that most CDOs themselves define two main responsibilities for themselves. 67% believe that their task will be to lead changes in the company related to the creation and maintenance of enterprise data systems and their analytics. 61% believe that they will have to integrate analytics and data into the strategy of the enterprise, its "road map." Most respondents also noted that they had a good relationship with IT management in the company. However, analysts clarified that with the growth of the powers of experts on big data, their relationship with information technology directors (CIO) may deteriorate due to disagreements in strategic development and decision-making priority.

How does an enterprise data management strategy help transform your business? TADetali

The need to digitalize the business is increasingly pushing Russian companies to develop their own data management strategy. However, it is difficult for many enterprises to decide on a new approach to working with corporate information due to the outdated IT infrastructure. What to do with this, whether it is possible to implement the project on its own and how Data Governance helps to unite business and IT, the experts of the company "Krok" helped to understand: the head of the "Storage Systems" direction Vladimir Kolganov and the expert of Big Data practice Yegor Osipov. Read more

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

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

Notes