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?