The Hows, Whats and Whys of Data Governance

Share on facebook
Facebook
Share on google
Google+
Share on twitter
Twitter
Share on linkedin
LinkedIn
Share on reddit
Reddit

In order to understand why your organisation should have a high-quality data governance policy in place, it’s essential that you have a good idea of not only how to get started, but why you should get started. This post is a rundown of all the basics of data governance – what it is, why businesses should make it a priority, and how to implement a good governance policy. In this post by Elizabeth and Jen, read more about how to get started on your program.

 

What is data governance?

 

Data governance is a term used on both a macro and micro scale. On a macro scale, data governance is a political concept that forms a significant part of overall internet governance. On a micro scale, it’s a management concept that forms part of corporate governance. Overall, data governance is a way of exercising control over the management of your business’ data assets. This includes planning, monitoring and enforcement, and ensuring appropriate availability, usability, security and integrity. GDPR law stipulates that all businesses should handle their data in a way that is appropriately secure and adhering to specific laws, and a data governance policy can significantly help with keeping on top of this and ensuring that regulations are being kept to.

 

A data governance policy should help everyone in your business to be aware of and capable of good data management. This allows everyone to be aware of the risks involved in poor data quality, and accountable for the adverse effects. 

 

Why is a data governance policy important?

 

There are a number of important reasons why any business should have a data governance policy in place. 

 

Having a policy in place is especially important now that data storage policies have changed in recent years. Data is no longer only accessible to IT and data management staff; data is now more likely to be stored in massive data warehouses, which are accessible to and used by a much wider range of people within the workplace, not all of whom might be as knowledgeable as those with data management expertise.

 

A common organisational goal is to break down data silos and stop them from building up until they become more difficult to work with. Different business units will use different processing systems, and without a centralized framework in place an organisation’s data can become disjointed and very hard to manage. A data governance policy can help to harmonize your data.

 

A data governance policy also ensures that data is used correctly. It can help to prevent the introduction of errors into systems, and block any potential misuse of confidential or sensitive data, or anything that could breach GDPR regulations in any way. Creating and enforcing company-wide standard policies and procedures as part of a data governance policy will work wonders for reducing bugs in the system and breaches of privacy.

 

Having a data governance policy in place can also lower a business’ data management costs. With standardized regulations and procedures in place, the effort involved in managing data is reduced, because processes are streamlined and mistakes are less likely. As well as being an essential part of maintaining appropriate data management techniques, a data governance policy can save an organization a lot of time and money.

 

Similarly, good data governance results in increased and easier access to critical data for data scientists, analysis, and IT professionals within your business. Less time searching for data and stressing over whether or not the data in question is in-line with GDPR means that they can do their jobs better, while also having more time in their day to extend their expertise to other tasks too. 

 

Good data governance is also very likely to drive better decision making in a business. Executives will have access to better quality information, and more time can be devoted to making the best decisions possible if less time is being spent trying to fix mistakes or data breaches.

 

How can you get started?

 

It is essential that the owners and custodians of a business’ data are involved from the beginning in implementing a data governance policy. This should also extend to all levels of a business, with colleagues who work with the data also being involved in the process. Ideally, a data stewardship role should be appointed at this phase of the process, so that the policy is being used by someone who has experience of it from the early stages. Legal teams and those working in compliance should also have a say — including, of course, GDPR Officers. Overall, everyone’s understanding of the policy should be aligned from the start. Similarly, it is worth considering involving data owners, and potential data owners, as they are important stakeholders who would be likely to appreciate having a say in the new initiative.

 

Furthermore, processes should be defined for storage, archiving, and backing up of data. An important part of data governance is protection from theft, attacks and, most likely, mistakes. These processes should all be made as clear as possible to anyone in the organization who would benefit from being aware of them.

 

Similarly, a code of best practice should be created and upheld at the beginning. Business managers, data managers and IT staff should all learn the best practices of data governance, and everyone who deals with data in any way should learn about GDPR compliance and being responsible with the data they come across. 

 

Often, IT teams and data scientists can be wary of data governance policies, despite their importance. This is partially because they can be concerned that colleagues will see the policies as unnecessary, and see their colleagues in IT and data as being “data police”, breathing down their necks and being overly critical. A way to combat this outlook is to ensure that your business’ data governance policy is business-driven rather than driven by IT teams. Colleagues are less likely to be resistant if policies appear to be implemented by the business as a whole, rather than one specific team.

 

Similarly, when getting started with a data governance policy, the initial project should be driven from the top down. The governance model should align with the organization’s priorities, and any other parts of the model should be built on from there. For example, a BI data governance policy should identify reports that are a top priority for the business. Overall, a governance model should be built around critical data elements.

 

Keep Exploring

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

© Data Relish. All rights reserved