Author: Amélie Van Hoecke
In our previous article, we discussed hidden data and the cost associated with it. Drawing fact-based conclusions, recommending the right product, and creating meaningful dashboards are all actions that require good quality data. However, the stark reality in many companies is that data is not accurate, incomplete, and even inconsistent between various applications/departments. The reason being that data systems are often added on top of each other and this in different formats, thus resulting in retrieval of information being close to impossible. Additionally, data and data-knowledge are often scattered throughout the organization, whereby nobody is responsible for end-to-end data flows and full overviews are non-existent.
Most companies agree that their data is precious. However, they underestimate the costs associated with their data not being appropriately managed. To enable your organization to capture the full potential of data and maximize on utilizing employee productivity; the solution is data governance.
What is data governance?
Data governance is relatively straightforward. By providing the right organization, tools, and metadata, companies are able to keep their data under control. Governing your data should be done the same way libraries manage their books. If you would like to find a book in your community library, you do not start searching at random. Instead, you ask the librarian, or even better, you use your library’s search engine to look for the book based on the title, author, publishing date, etc. It does not really matter where the book is stored in the library; with the right support and information, you are able to find it in no time.
Extrapolating from this example, a structured library is precisely what data governance should provide you with, except that instead of books, we have your data.
In essence, data governance is a systematic approach to bringing order to your data to make it sustainable. It acts as the bridge between the business imperatives and the technical reality of systems. At BrightWolves-HighMind, we approach it in three parts:
Documentation: reports, dictionaries, policies to provide the information on your data and metadata. This includes, amongst others, a business glossary with definitions of the data elements, a report catalog providing you with the existing reports and their usage, as well as a KPIs catalog that defines the measurements used in the different reports.
Methods and tools: including collecting, retrieving, and updating the data and metadata. A data governance tool is needed to support all documentation materials and ensure consistency over the enterprise and throughout the digital transformation.
Organization: the data professionals that will manage the data and design, configure, and use the data governance tool. Roles you come across are data stewards, data engineers, data custodians, etc.
Lastly, the data professionals will, in turn, perform quality control and keep the documentation up to date.
At BrightWolves-HighMind, we have already helped several clients in setting up overall data management strategies and implementing data governance by focusing on these three aspects from a technical and a business point of view.
Would you like to know more about data governance? Are you ready to fully tap into your data? Feel free to reach out, I would be more than happy to further discuss the possibilities that await you.