How Data Governance is Central to Effective Data Analytics

In the publishing industry, there are a lot of things we can measure. However, if there is no strategy underlining how and why we collect data and who can access it, the value is lost. Not only that, but we can put our business at serious risk of non-compliance. Ultimately, data governance is central to effective data analytics and underpins everything we do. 

In this article, I’ll explain the importance of data governance having a seat at the table with top business executives, including how a unified data governance strategy supported by secure, scalable systems delivers immense value now and in the future. 

When it comes to data, the first question isn’t whether you can measure something; it’s whether you should. It’s vital to ask yourself what your business model is. After all, it takes money to create content. There is a big debate in many publishing houses as to whether people should be allowed to access data if they don’t accept cookies. If you can’t measure what those consumers are doing and why, then do they still provide business value? If not, the business model needs to change. A lot of companies are trying to navigate the same landscape and there isn’t a single standard on what you should do. Ultimately, while respecting regulations and people’s right to privacy, you need to consider the business value of data. In our industry, sometimes content is given away for free and money made through advertising and at other times, content is subscription-based; what is true in both instances is that data governance informs that choice. 

What you can measure or should measure hugely impacts what you can do as a business and can create a significant shift in your business model. Ultimately, you can’t run a business if you’re not sure about what you can measure and what the regulations are in terms of data governance. That’s why I’m such a huge advocate of data governance having a seat at the table with top company executives; it has to underpin the business model and business strategy. 

There have been a lot of changes in recent years from a privacy perspective, with GDPR and other regulations coming into force. To be compliant, every business needs to be aware of what data they measure and store and who has access to it. Data governance is there to ensure people only have access to the right thing, with the right controls in place to prevent any violations of that. It’s vital to ensure people’s privacy and data are protected, with no chance of it being misused. After all, getting it wrong has serious legal, financial, and reputational implications for individuals, businesses, and society as a whole. 

To be able to manage the legal aspects of external data governance, having a strong legal team is fundamental. Having a data privacy group within your legal team can help you really understand risk and interpret what the law means for your business. It’s no mean feat, of course. There is no one regulating body and the rules from one country to the next can vary greatly. It’s extremely complex to navigate, which makes having data privacy experts on hand, and a legal counsel in particular, invaluable. 

Meanwhile, internal data and accessibility need to sit as a data function within the technology team. There has to be a specific group, a data team, that ensures a business collects, surfaces, and stores the right information and makes it accessible. Only then can a data analyst or data scientist interpret that information and create business value. 

If your employees have to search through thousands of columns of data that have no impact on their role, they are wasting time. It’s like trying to find a needle in a haystack. By having the right policies in place to say who should have access to what data, you can avoid that problem.