Data Discovery Automation
Learning from the Warehouse Experience

By Barry Devlin, 9sight Consulting




Data Discovery Automation
Learning from the Warehouse Experience

As data discovery becomes increasingly important for insightful and pervasive decision making and draws data from ever more sources, business must face the issue of managing the population of these environments. This leads to the concept of governed, agile data discovery to ensure clean, consistent data for the business and to avoid a spaghetti-like population architecture for IT.

This paper proposes that such governance demands the creation of a Discovery Hub. This is a data store where core business information can be cleansed, reconciled, and made available as a consistent resource to data discovery users, while allowing them the freedom to source other data they need elsewhere.

Beyond defining the Discovery Hub, we further suggest that the best approach to populating this Hub, as well as the downstream data discovery environments, is via Data Warehouse Automation (DWA) approaches and tools.

Finally, we describe TimeXtender’s Discovery Hub® software and how it addresses the requirements and implementation aspects of the Discovery Hub architecture in conjunction with a variety of data discovery tools.


  • The Whys and Wherefores of Data Discovery
  • Introducing the Discovery Hub
  • Automating Discovery Hub development
  • The Discovery Hub in practice
  • Conclusions 

Read more about TimeXtender's Discovery Hub® here.


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