Data governance foundation to enable proper data use: Interview with Ole Busk Poulsen


Although data governance initiatives are usually started to fulfil external regulations and requirements, it’s so much more than security and compliance. It’s fundamental business hygiene that helps us do our business in an effective and efficient way. When we take into account the sensitive data that banks deal with and the highly-regulated industry, it’s expected that a lot goes into creating a sound data governance framework that would support banks’ work. Ole Busk Poulsen, Head of Data Governance & Information Architecture at Nordea, will be talking on this subject at the Data 2030 Summit, focusing on data ownership, how to build data governance capabilities and how to get started with data governance in the first place.

As a warm-up, Ole took us to the basics with establishing data governance in banking in our discussion before his presentation.

Hyperight: Hello Ole, we are really glad to welcome you as a speaker at the Data 2030 Summit 2021. Please tell us a few words about yourself and your background.

Ole Busk Poulsen, Head of Data Governance & Information Architecture at Nordea

Ole Busk Poulsen: I’ve actually worked with data my entire career. After a few years in the software industry, I moved to banking. For about 10 yrs I worked with data warehousing with special focus on the user perspective. The work was focused on mapping of business rules, modelling of end-user data, training of end-users etc.

Then before it was even called data governance I started working with disciplines like business metadata, data quality etc and used that as a foundation for the first data governance initiatives.

Since then I’ve now been part of two other data governance initiatives in different companies. I’ve worked with data governance in an IT organisation as well as in a business area, and I have to say, that it gives different perspectives depending on where you have your starting point.

Data governance foundation to enable proper data use: Interview with Ole Busk Poulsen
Photo by XPS on Unsplash

Hyperight: Banks are under very strict security and compliance regulations as they deal with very sensitive customer data. How data governance and data quality help banks meet these regulations and manage risk?

Ole Busk Poulsen: Data governance is a hygiene activity. It is something we need to do to run our business in an effective and efficient manner. Fortunately, it will also help us fulfil external regulations and requirements. If we only focused on the security and compliance regulations it would be the same as only cleaning your house when you have guests. So data governance and data quality are business disciplines that support us in the daily work, which includes being compliant. To be a bit more specific it helps us in understanding the content and quality of the data that we have as well as interpreting them in a given context. When we understand that it is easy to assess if a given set of data is fit for a business purpose. That being said, data governance gives banks the transparency of data content, quality and context needed to meet regulations and manage risks.

Hyperight: What are the main requirements for a comprehensive data governance framework in the banking industry and financial institutions?

Ole Busk Poulsen: First of all a good data governance framework should cover both the building and the maturing of the data governance capabilities and the execution of data governance in daily work.

Secondly, it should describe how you want to align across the organisation as well as how you get physical data under governance.

On the more practical side, it is important that the framework is very clear on roles and collaboration. Often we have situations where we have specific data governance roles with a given responsibility, but often we also have generic roles where we also place responsibilities for certain data governance activities. These responsibilities and roles must be very clear. Another perspective on this is the collaboration between the roles. When we execute data governance we often work across the functional areas in the organisation. In order for that to succeed it is paramount that the collaboration and decision making is well defined and transparent.

Other important elements of a data governance framework are: common vocabulary, data lineage and data quality.

Data governance foundation to enable proper data use: Interview with Ole Busk Poulsen
Photo by Andrea Piacquadio from Pexels

Hyperight: How do you measure the effectiveness and impact the data governance initiatives?

Ole Busk Poulsen: I think it is important to note, that before starting to talk about effectiveness and impact, we need to realise, that often we have to start by building the data governance capabilities. We cannot discuss the effectiveness and impact before we have some basic capabilities in place. Basically, we need to be able to support that the organisation works with data in a much more mature way. That is why we should see data governance as a business transformation process.

If we only focused on the security and compliance regulations it would be the same as only cleaning your house when you have guests.

So in the initial phase of data governance, we need to measure the capability building. Here we have measured e.g. the number of data with an appointed owner and how far the owner is in building the operational data governance for the data. What we started measuring now is the data quality perspective, i.e. whether data quality is managed, and if we improve the data quality.

What we ultimately want to measure is if we solve real business problems and if we improve our ability to reuse. But before we can do that, we need to take the next steps in developing the capabilities.

Hyperight: Your session at the summit will focus on How to build the foundation for ready to use data. Could you tell us a bit more about what the audience will be able to take away from your session?

Ole Busk Poulsen: One of the key topics in my presentation is data ownership. It is not easy to identify the right owner of data and where in the organisation to look. I will present different perspectives that we have tried and what the pros and cons are with the approaches. At the same time, I will link the data ownership discussion to the maturity of the organisation.

Another key topic is how to get started. One thing is to have the owner and other roles in place, but if they don’t know what to do, then you will not get far. So I will explain how we build the foundation and got the operational wok up and running.

Hear the latest methodologies, strategies and tools used by organizations discussed by the brightest minds in the Data Management community. The Data 2030 Summit focuses on the fundamental pillars of a modern data management strategy: Data Governance & Data Quality, Cloud or Multi-Cloud enabled infrastructure and DataOps (+Master Data Management) wrapped in a three-day extensive programme.

Featured photo by Alex Shutin on Unsplash

Chief Editor at Hyperight Read. Reading and writing are her passion. Claims typing on a keyboard calms her down. Enthusiastic about Data Science, AI, Machine Learning and all things digital.

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