Governance for Modern Data Estate

The objective of this blog is to cover the basics of data governance, why data governance is important, who should invest time in data governance and once decided, how can one start the data governance journey.

When I started to write the blog, I looked up for the proper definition for data governance on the internet, I realized, all the definitions talk about three or four core aspects. I particularly liked the following few definitions -

People, processes, policies form the core of data governance backed by technology.

We can go straight into defining the RACI for each of these pillars and how to manage the distributed data landscape with the help of robust data governance technologies available in the market.

But before going into the solutioning, let us understand the problem statement.

This cartoon really sums it all up.

Any persona in a decision-making position in a company - be it CEO, CDO, CFO – who make decisions which may cause substantial profits or loss to a business or a data engineer who needs to decide on whether to go ahead and change in an ETL transformation without affecting other areas of data estate, would rely on some kind data heavily to make their decisions. The effectiveness and the success factor of that decision is directly related to the trust that the persona has on the data that was used for decision making.?How do they get the trust to make the decision is when they are aware of where the data is coming from, what are the transformations it has gone through, is it complete information, is it cohesive etc. If the decision maker has answers to all the questions and has a view of data under the hood, then we can consider the data is trustworthy.

Now, all these questions are answered quite effectively when there is an effective data governance process, supporting technology and tools for data governance and a data governance culture within an organization.

With that, now we established why we need to govern our data. Let us now understand is this required by all business? Small or big??

With the statements like these from industry leaders of non-technology sectors, it is evident that it is the era of digitize or die for businesses of all sectors. Organizations can no longer afford to ignore dramatic changes in the way customers are looking at products and services but to adapt to them urgently. Chief Data Officers (CDO) of companies are forced to think of becoming digital-first and are starting to embrace the latest technologies like cloud computing, AI/ML and are accelerating their transition to a data-driven culture.

If you are a small company who has just started up or a big company who has been running the business for several decades, data is the core of any business now. The importance of data governance will increase over time, and any forward-thinking organization that needs trustworthy data to make accurate, data-driven recommendations/decisions must consider how data governance can help them reach their goals.

After establishing the WHO factor, a question one should ask themselves is?- why are we planning for governing our data? We end up with responses like -

1. To Protect our data
2. For compliance with different regulations
3. Improve the quality of our data
4. Understand our data and its origins
5. Improve access to data

While all of these reasons make sense, we would argue that the core motivation for implementing a data governance program is often unclear. Over the last few years, I have witnessed many failed data governance implementations. By failure, I mean being unable to get a return on the investment made.

Data governance technology/tool is be implemented by IT team but generally speaking, the business is really not engaged. And the result of all these efforts?

Eventually, data governance becomes more of a bureaucratic ‘must-do’ than a business ‘want-to’. The reason for this is so often linked to the question?WHY?

Often, the focus of data governance programs is on putting controls in place rather than on promoting the use of data. After all, if what we are doing is not directly related to creating value for the company, then why do it?

These are some of the questions that organizations need to brainstorm and answer as to WHY they are intending to govern their data.

Once we have an answer for ‘why data governance?’, you create a statement that emphasizes usage, trust and value. It takes you away from the ‘command and control’ mindset that prevails today. It’s a great starting point to get senior management and business on board to pull the initiative rather than old fashioned push approach by a centralized data governance team. Implementing a data governance program is a complex initiative involving a transformation mindset that is based on, and supported by, smart technology. Getting the WHY right and communicating it across the organization is key to getting a good start. But of course, it doesn’t stop there.

Above mentioned are some top tips that we could use to create ongoing success for the businesses:

1. Define the WHY with your key stakeholders and communicate it across the organization.
2. Get a sponsor who understands the context.
3. Believe it or not, data governance is in place even if it isn’t. Try to integrate with existing initiatives rather than ‘reinvent the wheel’.
4. Replace the often-stagnant data stewardship approach with a more agile and self-organizing one, if the culture permits it.
5. Strive more for ongoing progress rather than perfection.

After establishing right answers for who, why and how, we now decide to embark on the journey of data governance. But where do we start from??

There are several industry frameworks, guidelines, best practices laid out by associations like DAMA, councils like CDMC, big 4 consulting firms and technological research firms such as Gartner. There are several guidelines available if one chooses to start consciously, governing their data. DaMa DMBok wheel is one such reference.?

Having worked with several customers across different domains like large banks, telcos, retailers, public sector like governments, education, health industries to small and medium scale customers like schools, startups and unicorns, and witnessing customer’s pain points and where they need help personally. As as result, I have highlighted some of the areas where customers have mostly struggled -

Upon understanding WHAT, WHO and WHY data governance, one can infer that data governance is not primarily a technology conversation but a conversation for organizational cultural change. Customer intends to digitize the tribal knowledge within the company to institutional knowledge using a relevant technology backed by relevant people, process and polices.

Conclusion

This blog is my attempt to translate my experience gained while working with varied customers on their data platforms, seeing their problems first-hand and helping them to solve it. If you think this article was helpful, please give it a thumbs up and share your views in the comment section, thank you!

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