Learn how Snowflake, Databricks, Amazon Redshift, Microsoft Azure, Google BigQuery and InterSystems perform running large-scale analytics with and without a semantic layer at scale.
Schedule a live demo to learn more about:
What a semantic layer is and why would you want one
How using a semantic layer impacts cloud data warehouse performance and cost
Why your semantic layer should be independent of your BI tools and data platform
Where a semantic layer fits in your data & analytics stack
Learn how a semantic layer
Decouples the analytics consumption layer from the cloud data layer
Delivers a business-oriented model of cloud (and multi-cloud) data sources
Presents a consistent view for BI and Data Science teams to consume with tools of their choice
Manages and optimizes analytics performance on cloud data
WORKING WITH DATA-DRIVEN TEAMS
“Data and analytics leaders must adopt a semantic layer approach to their company data assets or face losing the battle for competitive advantage.”