The Practical Guide to Using a Semantic Layer for Data & Analytics

Learn how and why the world’s most data-driven organizations use a semantic layer for speed of thought query performance and consistent KPIs across all of their BI/AI tools, such as Excel, Power BI, Tableau, Looker, Databricks, DataRobot, and H20, using a live data connection to Snowflake, Google BigQuery, Databricks, Amazon Redshift, Microsoft Azure Synapse and more.

Download this guide for practical advice on how to use a semantic layer to unlock data for AI & BI at scale. You’ll learn how a semantic layer delivers massive ROI with streamlined query performance, concurrency, cost management, and ease of use.

Read this guide to learn:

  • How to make better, faster, and smarter data-driven decisions at scale using a semantic layer.
  • How a semantic layer delivers massive ROI with streamlined query performance, concurrency, cost management, and ease of use.
  • How to enable data teams to model and deliver a semantic layer on data in the cloud.
  • How to achieve speed of thought query performance and consistent KPIs across any BI/AI tool, such as Excel, Power BI, Tableau, Looker, DataRobot, Databricks and more.
  • How you can reach optimal performance on large datasets while improving query performance and user concurrency by 10x.

Get It Now!

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.