Demand Side Data Management comes from the notion to provide value to customers as our highest outcome and has been around as a concept for demand side data quality for a while. We let the consumer decide what data quality he needs to create value with the data.

•  But can we widen that approach to a Data Management as a Service model?
• Can we put Data Management into a chain of custody?

Aiko Yamashita, Senior Data Scientist at the CoE at DNB, and Karl-Aksel Festø, Head of Advanced Analytics CoE at DNB, gave their input to these questions, supported by examples form their work at DNB.

 We talked about:

• What is the difference between Data Science and Analytics?
• What skills do we need to build data literacy?
• How do we get from analysis to insight, and how do we get from insight to action?
• Who is demanding Data Management?
• How is Data Management linked to the data value chain?
• What does it mean to manage a non-depletable asset that is a common good for many different stakeholders?
• What is the value of good Data Management?