2022. jan. 21.2 perc olvasás

Move from technical to strategic data governance

Digitization has placed data at the heart of organizations' initiatives, both for operational and strategic needs. As companies capture massive amounts of data and deal with big data environments, they must maximize their value, manage risk and reduce costs using a sharp data governance policy and strategy.

What is the role of data governance?

The primary role of data governance is to ensure that organizations have accurate knowledge of data and precise processes in place for securing the quality and use of their data. Data governance is about who owns the data (data owners), which data is available for businesses and where it is stored (data catalog and data assets), and how to make it compliant (data regulations, quality, and security).

Building a relevant data governance strategy means organizations need to not only clarify operational needs but also connect the approach to business goals.

Defining a global data governance strategy

Data is part of intangible assets and its extensive use has given rise to the concept of "data-driven" companies. The expression is often misunderstood by those who refer to a stack of technologies and "pipes" to transfer and process data. However, the traditional, monolithic, and outdated approach to data governance does not always produce the benefits needed in today's business world.

Successful organizations have been able to put technology at the center of their business strategy. They have gone beyond strictly operational needs to implement a real innovation strategy based on the use of data. But to meet data governance challenges, organizations must take a holistic view. Those who successfully converted to a data-driven approach treat data in a business context. Above all, it is a question of answering business needs, such as optimizing customer journey or the hyper-personalizing experiences provided to customers.

Involving business lines in a data governance policy

This is the strategic challenge and the most difficult dimension of data governance. The first step is to manage and control captured data, from discovery to usage, through its classification in a catalog. But this process will remain incomplete if the chief data officer has not identified the business owner of the data. Successfully involving businesses in data governance is a strategic challenge and is certainly one of the most complex dimensions of this type of project.

For maximum efficiency in data governance, organizations need to have a single, reliable source for all stakeholders. This is an essential aspect that allows everyone to share a common language and develop confidence in the quality of the data. Both points are critical for organizations to take full advantage of data-driven value. To meet these needs, a collaborative platform proves to be the most effective solution to build data governance. It ensures that all parties handling data have the same level of information, and business analysts have reliable data to make decisions that drive innovation. Ultimately, the search for efficiency and innovation using data cannot succeed if the stakeholders are not informed and involved. Moving from technical governance of data to strategic governance is the clear path for organizations that are ready to turn their data into a strategic asset.