How can you benefit from a Machine Learning Data Catalog?

You can use Machine Learning Data Catalogs (MLDCs) to interpret data, accelerate the use of data in your organization, and link data to business results. 

We provide real-world examples of the smart features of a data catalog in our previous articles: 

It is clear that this data catalog specificity is a cornerstone in choosing the right data cataloguing solution. In fact, Forrester highlights exactly that in their latest report: “Now Tech: Machine Learning Data Catalogs, Q4 2020.” 

In this document, they cite Zeenea Data Catalog as one of the key Machine Learning Data Catalog vendors on the market! However, as data professionals, you are aware that the “intelligent” aspect of a data catalog is a good solution, but not enough for you to achieve your data democratization mission.


Machine Learning Data Catalog vs Smart Data Catalogs: what’s the difference?

The term “smart data catalog” has become a buzzword over the past few months. However, when referring to something being “smart” most people automatically think, and rightly so, of a data catalog with only Machine Learning capabilities.

We at Zeenea, do not believe that a smart data catalog is reduced to only having ML features! In fact, there are different ways to be “smart”. We like to refer to machine learning as an aspect, among others, of a Smart Data Catalog.

The 5 pillars of a smart data catalog can be found in its :

  • Design: the way users explore the catalog and consume information,
  • User experience: how it adapts to different user profiles,
  • Inventory: provides an intelligent and automatic way to inventory, 
  • Search engine: meets different expectations and gives intelligent suggestions, 
  • Metadata management: a catalog that marks up and links data together using ML features.

This conviction is detailed in our article: “A smart data catalog, a must-have for data leaders” which was also given last September at the Data Innovation 2020 by Guillaume Bodet, CEO of Zeenea.