Data governance should be on top of any C-levels’ agenda, but more often than not it isn’t. In this article we will give you an overview of what data governance is and what it is not. What is data governance, why does it matter so much for data-driven companies, and how do they master this discipline?

What is data governance?

 

There are many definitions for data governance which already indicates the complexity of this topic. A classic often quoted definition states that “data governance is the overall management of the availability, usability, integrity and security of data used in an enterprise.”

According to Gartner, “data governance is the specification of decision rights and an accountability framework to ensure the appropriate behavior in the valuation, creation, consumption and control of data and analytics.” Equipped with these two definitions we can now dive deeper into the topic.

Data governance and compliance

 

When asking a handful of experts, you will most likely also get a handful of definitions or specifications of what data governance is. So basically, a big part of a good data governance is determining what data governance is in a given organization. While complying with legal standards in your business area is important, focusing only on pure compliance will not get you very far and will definitely not help you to take full advantage of modern data technologies.

Thus, simply complying with the vast numbers of data regulations is not a proper long-term data governance strategy. Examples of these regulations include the California Consumer Privacy Act, GDPR and the ePrivacy regulation that is still in the legislative process. So, data governance is not a fixed set of regulations, but can be seen as a fluid construct that needs to adapt when necessary.

To achieve compliance with these regulations, business processes and controls require a set of rules to be followed internally. They also need to be revised and adapted on a regular basis, if necessary. This is the role of data governance in modern, data-driven companies.

Why is Data Governance important for modern companies?

 

Companies benefit from good data governance, because it ensures data is consistent and trustworthy amongst other factors as we have seen above. This is critical as more organizations rely on data analytics to make business decisions, optimize operations, create new products and services, and improve profitability.

Since data can be a core part of what companies use to decide on or make a profit from, it is key to have an agreed upon data governance process and policy. It is also important in setting common goals throughout the enterprise, so everybody that works with data has the same understanding of the data-driven goals. Especially as technologies become more advanced and algorithms increasingly make decisions based on data on their own.

Advanced Analytics is required for complex tasks such as prediction, customer centricity, personalization and cross-channel attribution. This is not easy! Avoiding the effort or reducing complexity by oversimplifying the challenges is not an option when data is key to measure your success in terms of efficiency and effectivity, to understand your customers, to provide the best services and offers, and last but not least to drive growth and master your business goals.

The increasing demand of customer data platforms in order to meet privacy and security compliance requirements especially for personalization, marketing and advertising reasons is adding another important and complex layer to the data-collection, -processing and -maintenance. Understanding and managing such a data ecosystem is a core competence in a data-driven company. Data Governance is the process of choice to assist here.

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How can a good data governance be achieved?

 

There are multiple different data sources to integrate into an advanced data analytics or data management eco-system. Regardless if the data processing is more an ETL- or an ELT-process (e.g. for feeding a data warehouse vs pulling data from a “data lake”), it requires good technical and procedural standards as well as fast and automated data-processing. Everybody in data and technology knows about the garbage-in-garbage-out problem and decision cycles taking longer than an action can wait.

While data governance initiatives can be driven by a desire to improve data quality, they are more often driven by C-level executives responding to external regulations. A 2017 survey investigating data governance by surveying CIOs found, that 54% stated the key driver was efficiencies in processes while 39% said it was regulation driven. Only 7% answered that their key driver was a better customer service. So, there is still a lot of companies that don’t take advantage of data to improve their overall customer experience. It is recommendable to not only use data governance to avoid fines, but to make a meaningful contribution to improve the business.

We have talked to 4 top-notch experts in this field and asked them about data governance, what it means in detail, how to master it and what needs to be done to improve. Their tips and insights will help you to start implementing data governance processes that accelerate your businesses data and analytics efforts.