Liliendahl on Data Quality

Earlier this year Gartner published a report with the title Top Trends in Data and Analytics, 2023. The report is currently available on the Parsionate site here.

The report names three opportunities within this theme:

• Think Like a Business,
• From Platforms to Ecosystems and
• Don’t Forget the Humans

While thinking like a business and don’t forget the humans are universal opportunities that have always been here and will always be, the move from platforms to ecosystems is a current opportunity worth a closer look.

Here data sharing, according to Gartner, is essential. Some recommended actions are to

• Consider adopting data fabric design to enable a single architecture for data sharing across heterogeneous internal and external data sources.
• Brand data reusability and resharing as a positive for business value, including ESG (Environmental, Social and Governance) efforts.

Data Fabric is the Gartner buzzword that resembles the competing non-Gartner buzzword Data Mesh. According to Gartner, organizations use data fabrics to capture data assets, infer new relationships in datasets and automate actions on data.

Data sharing can be internal and external.

In my mind there are two pillars in internal data sharing:

• MDM (Master Data Management) with the aim of sharing harmonized core data assets as for example business partner records and product records across multiple lines of business, geographies, and organizational disciplines.
• Knowledge graph approaches where MDM is supplemented by modern capabilities in detecting many more relationships (and entities) than before as explained in the post MDM and Knowledge Graph.

In external data sharing we see solutions for:

• Sharing the burden of collecting business partner records like CDQ.
• Sharing product information in business ecosystems as examined in the post What is Collaborative Product Data Syndication?

External data sharing is on the rise, however at a much slower pace than I had anticipated. The main obstacle seems to be that the internal data sharing is still not mature in many organizations and that external data sharing require interaction between at least two data mature organizations.