The Importance of Data Governance

Culture & performance



What is data governance?


Data governance has gained prominence over the past few years as a key aspect of doing business across various sectors. It refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. It is a key aspect of quality control which ensures that companies have reliable and consistent data sets to assess performance and make management decisions.


“Data governance is a set of controls and standards that ensures that your data assets are formally managed throughout the enterprise. So, what we’re talking about here is understanding the data flow processes, business rules, data definition and ensuring that they’re correctly applied.  The key driver behind data governance is to ensure we trust our data model.  By far, the main thing that people say to me is ‘We need to ensure that we have data integrity.”  Sam Vadodaria


Why is data governance ignored?


More often than not, this critical aspect of the data collection and handling process is overlooked, in favour of the aspects that generate fast, tangible results. Unfortunately, this is akin to putting so much emphasis on the main structure of a magnificent edifice because it is visible to the world, but ignoring the foundation which lies covered by the ground because it largely remains unseen.

To address this issue, we are going to do a short expose on why data governance is important to you as a business executive, and why the success of your company depends, to a very large extent, on the accuracy and fidelity of data availed, to inform and back up business decisions.


A lot of BI projects fail because they focus on technology. So, if we think about Microsoft’s Power BI tool, it’s evolving into a very good BI tool.  But, that alone across your business is nothing more than Excel on steroids! It doesn’t mean that you’re going to be making any better decisions based on anymore trusted data than you were with Excel.  It may look easier.  It may offer you a bit more interactivity, and it may be able to be delivered on an iPad but, without trust in that data, businesses can still be making the wrong decisions, and certainly losing trust from the people that use that data” Matt Simpson


Data Governance and Business Intelligence

Business Intelligence (BI) has grown in leaps and bounds in the past few years of the last decade. To define it in a simplistic manner, BI refers to the deployment of technology and attendant tools to avail and analyse data which is used in the making of business decisions. Business intelligence centers of excellence have gained traction as a key department in the structure of any corporation worth its salt. With the market moving towards automation and self-service to reduce the human interaction element in most transactions, thus making it faster and more efficient, data governance is set to play an even bigger role in the day to day running of businesses than ever before.


What challenges arise from data governance?

Data governance is a system, made up of many parts which ultimately come together to form the foundation of sound business decisions. Each business therefore needs to put in place its own system, which governs data collection and utilisation in a manner that advances the goals and objectives of the enterprise. Failure to do so can result in confusion and inefficacies in the business environment. To quote one industry expert, Gary Nuttall, in a recent interview, “Data Governance is critical to the success of BI and analytics.  If a firm can’t agree up front what basic terms means across the enterprise; “Customer”, “Sales Revenue” and “Profit” being obvious candidates, then how can you analyse them?  If there aren’t mechanisms in place to identify critical data, provide definitions (e.g. a glossary), ownership, quality criteria, lineage etc. then it will quickly fail.”


Four main challenges arise in relation to the governance of data available or collected by an enterprise;


Accuracy of data: The accuracy of data collected can only be as good as its source. If erroneous data is collected, even the best analysts in the world would never make it work for the enterprise involved. That means that every serious enterprise has to put in place a system that collects accurate and verifiable data. Peter Thomas, a leading industry expert had this to say on data analysis in a recent interview. “The money that’s ploughed into tools and into infrastructure is not matched by investments in data quality improvement or ongoing data governance. And so, if you don’t look at those types of things, you’ve, unfortunately, got a sort of garbage in, garbage out approach. And if you have the best tools in the world, in terms of what you’re trying to do to set up your data, if your data is not that great to start with, then you’re going to have a problem.”


Data Security: The security of data collected by an enterprise remains one of the biggest concerns, especially in the current digital age. Previously, prior to digitalization, the greatest threat to the breach of data security was a break in and the theft of company files. The digital age has however ushered in an age where digital data can be breached remotely through hacking with devastating results.


Data analysis: Data analysis is the part of the process which breaks down information and presents it in a manner that is practical and usable for an enterprise. The recent meteoric rise of business intelligence means that more technological experts and technological tools are deployed in business data analysis than business experts. Enterprises however now need to balance between the technical experts needed to run the technological tools deployed in data governance effectively, and business experts who are equipped with the correct tools of interpretation, to analyse the data availed effectively.


Data disposal: The disposal of data, once it has been utilized, or in the process of utilization, by an enterprise is one of the most daunting aspects of data governance. Privacy laws in most jurisdictions are very strict on the utilization, sharing and disposal of data. Every enterprise therefore needs to ensure that the data governance system put in place complies with the necessary regulations with regards to the usage, sharing and disposal of data.\


The importance of data governance


From the foregoing, it is clear that data plays a very key role in the successful operation of any business entity. It is therefore only fitting that a proper system is put in place to ensure that the collection, utilization and disposal of data is done within the law, and in a manner that advances the goals and objectives of a business enterprise. As a policy maker in a corporation, you need to ensure that proper data governance systems are put in place. These will be beneficial to the business by ensuring that;


  1. The data corrected is factual, correct and verifiable, which will give the business a sound foundation for important strategic decisions.
  2. Data analysis will be done in a professional way, which will give rise to proper actionable business projections.
  3. The business will minimise and mitigate the risks of data theft and the attendant breach of the obligation to protect private data provided by clients and customers.

In a nutshell, data governance is the foundation and the framework upon which a sound modern day business should be run. You need to ensure that your business is running on a strong foundation, if the enterprise is to have sustainable growth.



By Daniel Thornton

Head of Business Intelligence