The rise of data-driven companies has seen a surge in the popularity of data-driven projects. Data Governance. This type of initiative should not be understood as a ICT project but as a process of continuous improvement that affects the entire organisation. It is up to the management to lead this initiative and define the working teams to initiate the change.
By way of example, we could cite several lines of work related to Data Governance:
- When was my data created, is it still up to date, and am I using outdated information in my analytical processes? Apply strategies such as indexing company data sources, planning periodic data loads, updating analytical models, etc.
- Are the terms familiar to my business and does the whole organisation understand the term "Profit" in the same way? In the example "Profit" can be related to revenue - expenses, EBITDA, etc. -> Apply strategy of building a glossary of business terms to remove ambiguity from the language and keep it up to date and accessible to all teams.
- Is the data being used for what it was generated for, and does similar data exist in various information silos in the company? Implement strategy for defining functional responsibility for the data (Data Stewards) to ensure the correct use of the data and even improve the quality of the data through their specific knowledge.
Each of the above examples will entail an action plan, rules, procedures and regular monitoring by steering committees (C-level: CDO, CIO, CTO, CEO, CFO, etc.).
Scope of a Data Governance project
The scope of a Data Governance project affects the whole organisation, but in summary we would find the following members:
- People: they bring knowledge, skills and motivation. They are the most important asset.
- Procedures: defined to handle any situation that may arise.
- Data: it enables both the operational part of our business and the analytical part.
- Technology: automate tasks by reducing the cost and increasing the quality of the data used.
Finally, it is worth noting the Data Office as a key element for the success of such projects. The Data Office defines, implements and enforces the standards of the steering committees and identifies new opportunities for improvement that will be further evaluated in successive committees.
