In this issue we look at enterprise knowledge graph semantics, how to move to a distributed data mesh, a helpful case study on UX improvements, “best-of-breed” stacks, and personal data privacy, first party ads, and consumer contradictions.


A definition of “Enterprise” in EKGs

Enterprise knowledge graphs are on the rise, but terminology and even conceptual understanding is inconsistent. Dan McCreary’s article is a good place to start to organize your own thoughts before diving in…

Many people co-mingle the terms from open linked data world and the semantic web stack’s role with the concepts related to sustainability and scalability of enterprise knowledge graphs.


How to move beyond a monolithic data lake to a distributed data mesh

If you haven’t yet had a reason to develop a complete understanding of what a distributed data mesh is, or how it relates to looking at data as a product for multiple enterprise functions, there is a good chance you will before long. Some familiarity will be important for many roles beyond pure data management. This in-depth article by Zhamak Dehghani covers the why and how, and likely answers most questions you have.


Quantifying UX improvements

Nielsen Norman Group‘s Kate Moran presents a case study, with before and after screen shots and metrics, illustrating how an informed information architecture can increase customer self-service and improve both customer experience and sales efficiency.


Best-of-breed stacks

Debates on the relative merits of vendor suites versus best-of-breed application solutions have been going on for decades. The data was scarce and questionable, the arguments “qualitative”, and the conclusions invariably “it depends…”.

Scott Brinker has a lot to say about today’s version of this debate with the more complicated and flexible software architecture options available. For his latest post on the topic he came up with a great way to apply some neutral data to his view that stacks are growing and increasingly best-of-breed.


Also, on personal data, privacy, ads…


The Gilbane Advisor is curated by Frank Gilbane for content technology, computing, and digital experience professionals. The focus is on strategic technologies. We publish more or less twice a month except for August and December. We also publish curated content technology news weekly We do not sell or share personal data.

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