The Semantic Layer: Why It’s Critical to Analytics Success and Always Has Been



Some constructs are just classic, even if the names change over time; that goes double for semantic layers in the analytics world. Unmanaged data lakes may be flexible, but without a cogent semantic model, their usability plummets and so does their adoption. 

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Now available on-demand!

Join this webinar (preso & demo) featuring analyst Andrew Brust, to learn how semantic layers and metrics stores enable the data mesh approach to analytics and imbue it with a mechanism for robust governance and proper federation across the enterprise. 

You’ll also see how semantic layers are consistent with the concept of dimensional models, which have been critical to analytics since the very early days of BI. Tune in to learn how to create a single source for enterprise metrics, analysis dimensions, and model features — enabling business unit autonomy, with central coordination and consistency across use cases.

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In this webinar

You will learn about:

  • Understanding and generating the metrics needed by the business to understand the definition of success in their analytics efforts
  • The semantic data model that serves as the critical underpinning of a business-friendly view of data
  • Why business-relevant dimensions are so important, yet often neglected
  • Leveraging a semantic layer platform for creating an agile, data-driven organization that leverages a Data Mesh hub-and-spoke architecture
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Who should watch

Data, AI & BI leaders and practitioners (e.g., Chief Data Officers, data scientists, and BI/analytics professionals)