Knowledge graph

MDM and Knowledge Graph

Henrik Gabs Liliendahl1 Comment

As examined in a previous post with the title Data Fabric and Master Data Management, the use of the knowledge graph approach is on the rise.

Utilizing a knowledge graph has an overlap with Master Data Management (MDM).

If we go back 10 years MDM and Data Quality Management had a small niche discipline that was called (among other things) entity resolution as explored in the post Non-Obvious Entity Relationship Awareness. The aim of this was the same that today can be delivered in a much larger scale using knowledge graph technology.

During the past decade there have been examples of using graph technology for MDM as for example mentioned in the post Takeaways from MDM Summit Europe 2016. However, most attempts to combine MDM and graph have been to visualize the relationships in MDM using a graph presentation.

When utilizing knowledge graph approaches you will be able to detect many more relationships than those that are currently managed in MDM. This fact is the foundation for a successful co-existence between MDM and knowledge graph with these synergies:

  • MDM hubs can enrich knowledge graph with proven descriptions of the entities that are the nodes (vertices) in the knowledge graph.
  • Additional detected relationships (edges) and entities (nodes) from the knowledge graph that are of operational and/or general analytic interest enterprise wide can be proven and managed in MDM.

In this way you can create new business benefits from both MDM and knowledge graph.

Data Fabric and Master Data Management

Henrik Gabs Liliendahl3 Comments

Data fabric has been named a key strategic technology trend in 2022 by Gartner, the analyst firm.

According to Gartner, “by 2024, data fabric deployments will quadruple efficiency in data utilization while cutting human-driven data management tasks in half”.

Master Data Management (MDM) and data fabric are overlapping disciplines as examined in the post Data Fabric vs MDM. I have seen data strategies where MDM is put as a subset to data fabric and data strategies where they are separate tracks.

In my head, there is a common theme being data sharing.

Then there is a different focus, where data fabric seems to be focusing on data integration. MDM is also about data integration, but more about data quality. Data fabric takes care of all data while MDM obviously is about master data, though the coverage of business entities within MDM seems to be broadening.

Another term closely tied to data fabric – and increasingly with MDM as well – is knowledge graph. Knowledge graph is usually considered a mean to achieve a good state of data fabric. In the same way you can use a knowledge graph approach to achieve a good state of MDM when it comes to managing relationships – if you include a data quality facet.

What is your take on data fabric and MDM?