This buyer’s guide lays out key considerations for organizations looking to apply data virtualization to their analytics use cases. Along with key features and capabilities, you’ll learn about the difference between data virtualization and query federation, drill down on caching techniques and get a detailed feature ranking worksheet for evaluating vendors in the space.
Topics covered include:
We also point you to additional resources and further reading to help you as you continue your research.
By 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture.
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 www.atscale.com.
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.