Buyer’s Guide


10 Things to Consider When Modernizing Your Analytics Infrastructure

Learn the different approaches to selecting and implementing a semantic layer for your analytics stack to drive consistency, ease of use and trust.

  • The top 5 signs you need to invest in a semantic layer
  • How to get started on your search for a semantic layer solution
  • Key considerations for your semantic layer including tabular and multidimensional views, support for BI and data science workloads, easy model development and sharing, and query performance
  • Checklist for reference as you start your search

The ability to serve one unified data model for all business users allows them to use the right tool to solve the right problem without restrictions.

CHAD WAHLQUIST Director, Data Strategy and Analytics Technology Platforms

About AtScale

AtScale powers the analysis used by the Global 2000 to make million-dollar business decisions. The company’s Intelligent Data Virtualization platform provides Cloud OLAP, Autonomous Data Engineering™ and a Universal Semantic Layer™ for fast, accurate data-driven business intelligence and machine learning analysis at scale. For more information, visit

AtScale Product Overview

AtScale provides the premier platform for data architecture modernization. AtScale connects you to live data using one set of semantics without having to move any data.

Leveraging AtScale’s Autonomous Data Engineering™ query performance is improved by order of magnitude. AtScale inherits native security and provides additional governance and security controls to enable self-service analytics with consistency, safety and control. AtScale’s Intelligent Data Virtualization™ and intuitive data modeling enables access to new data sources and platforms without ETL and or needing to call in data engineering.