The title of this blog post is a topic on my international keynote at the Stammdaten Management Forum 2016 in Düsseldorf, Germany on the 8th November 2016. You can see the agenda for this conference that starts on the 7th and end the on 9th here.
Data Quality 3.0 is a term I have used over the years here on the blog to describe how I see data quality, along with other disciplines within data management, changing. This change is about going from focusing on internal data stores and cleansing within them to focusing on external sharing of data and using your business ecosystem and third party data to drastically speed up data quality improvement.
Industry 4.0 is the current trend of automation and data exchange in manufacturing technologies. When we talk about big data most will agree that success with big data exploitation hinges on proper data quality within master data management. In my eyes, the same can be said about success with industry 4.0. The data exchange that is the foundation of automation must be secured by common understood master data.
So this is the promising way forward: By using data exchange in business ecosystems you improve data quality of master data. This improved master data ensures the successful data exchange within industry 4.0.
Liliendahl on Data Quality 