Data Governance: what is it, what is the team structure at Metinvest Digital, and why Agile?
Note: 📅 Updated info as of June 2025
In today’s world, data defines business success. Its collection, storage, analysis, and usage require proper governance. That’s where Data Governance comes in. So let’s explore what Data Governance is, unveil the structure of the data management team, and find out why the Agile approach is crucial in this context. The answers to these questions are known by Oleksandr Perkhun, Head of the Data Management Center at Metinvest Digital, and Yevhen Cherkesov, Lead Program Manager at Metinvest Digital.
What is Data Governance?
Data Governance is a concept aimed at regulating and controlling data, ensuring its integrity, quality, availability, and security. It is also a set of rules, policies, and processes that enable effective and responsible data management within an organization. The main goals of Data Governance are to ensure data accuracy and integrity, maintain data security and confidentiality, ensure compliance with regulations and standards, enable the development of data science models, and optimize data usage to support business processes and decision-making.
«At Metinvest Digital, Data Governance manages the following business areas: procurement, production, logistics, sales, finance, and HR. Currently, we are implementing 6 large projects, consisting of 23 streams. Our data warehouse contains 3 terabytes of data, over 200 dashboards have been built, and more than 10 data science models have been implemented. These projects are being developed for both Ukrainian and foreign enterprises that are part of the Metinvest Group», said Oleksandr Perkhun.
The structure of the Metinvest Digital data management team consists of three areas:
• Data Science. Specialists in this unit develop predictive, optimization, and AI models. The models are created using the Python programming language. Development is carried out in Azure Machine Learning, which allows models to be deployed and integrated with other Microsoft Azure elements.
• Data Engineering. The main task of this area is to make the data analysis process as convenient as possible for analysts and to provide them with clean data in the required quantity. To achieve this, our engineers use advanced technologies to build ETL processes, Data Lakes, and DWH – Azure Synapse.
• Business analysis. Analysts transform business requests into the language of technology. Their main task is to assist in preparing specifications and technical requirements for our developers. Our colleagues interact with a vast number of different accounting systems. The most common are SAP, 1C, Oracle, and Azure SQL DB.
Metinvest Digital ensures effective data management and provides Data Governance according to best practices.
Why is the Agile approach important in Data Governance?
«Data Governance is a living process that requires constant improvement and adaptation. The Agile approach, which is based on iterations and aimed at flexible response to changes, is important for the successful implementation of Data Governance», noted Yevhen Cherkesov.
At Metinvest Digital, the Data Governance project lifecycle consists of 5 stages, namely:
1. Initiation, which includes pre-business analysis, selection of the Data Governance program stream, estimation of planning efforts, and decision-making regarding the need for PoC (Proof of Concept – validation of the feasibility of a business idea).
2. PoC, MVP (Minimum Viable Product) – if necessary. This stage includes feasibility validation, evaluation of the potential economic effect, and development of a plan to confirm the effect with the customer.
3. Implementation planning and formation of business requirements and technical specifications (TS).
4. Execution, which includes the project implementation itself, its testing, and the product development plan.
5. Completion. At this stage, deployment to the production environment takes place, the effect is confirmed by the customer, act signing is completed, and of course, the service is supported and developed (lifetime).
In Data Governance, we use the Agile approach with a sprint duration of 4 weeks.
The key benefits of Agile in Data Governance include:
• Fast start: Agile enables a quick launch of the Data Governance process and gradual development.
• Continuous improvement: Agile iterations allow for ongoing improvements to Data Governance, aligning with changes in business and regulatory requirements.
• Flexibility and adaptation: Agile allows the Data Governance team to flexibly adapt to changes and respond quickly to challenges.
Data Governance is a key aspect of effective data management in the modern business environment. Metinvest Digital understands the importance of Data Governance and has a team structure that supports effective data governance. Using the Agile approach in Data Governance enables the successful implementation of projects.
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