Everyone wants to be ‘data-driven’ nowadays. How this should be tackled is the main question. Determining the status of data as a permanent management topic through a top down approach is crucial. Only when it is clear at management level what data can mean for the company and what the benefits are anyone get to work with.
To organise the data governance within your company, a number of steps can be identified. These are the most important ones:
- Ownership and management: Who owns the data? Who manages the data? By establishing and recording good management and ownership, data standards and data access can be better regulated. Changes to datasets (by other operational (ICT) processes) are always submitted to the administrator. Of course, this only works if the data supports this. A data management policy like this is not possible without the support of the data owners. Only when the senior management stands behind the principles and ideas of data management and this translates into policy, is the value of the data for operational management really warranted.
- Quality: Do we have everything we want to know? Are there no flaws in it? Is the data correct, consistent, (timely) available, void of duplicates? These are the axes along which data quality can be measured. By initially focusing on completeness, correctness and timeliness, the quality of data can be increased relatively quickly and easily.
- Privacy: Privacy is all about data regarding people. It’s an essential subject in adhering to the compliance rules of the GDPR (General Data Protection Regulation).
- Security: Security plays an important part with all data. Who are the users and what does it take to make the data accessible to those who need the data and are authorised to use it?
- Interfaces: The connection between systems through which data is pumped is an interface. These interfaces become more important as more and more collaboration takes place across departments. A common platform in which data arrives and is retrievable, a data lake, is an important precondition for the successful execution of data management.
- Master data: Master data concerns the data that is used in multiple business processes. The quality and coherence of these data is considered important and must be managed in a holistic way.
- Metadata: Data about your data. What does this column name mean? What is the quality of this table? Which other data is it linked to? Metadata must be recorded properly and centrally.
If the above basic principles are set within your company, the value and effectiveness can increase very quickly. The Tesorion consultants have a lot of experience with the implementation of data governance.
Questions about this article?
Contact our specialist Edwin van den Heijkant.