Key Criteria for Evaluating Data Virtualizationv1.0

An Evaluation Guide for Technology Decision Makers

Table of Contents

  1. Summary
  2. Data Virtualization Primer
  3. Report Methodology
  4. Decision Criteria Analysis
  5. Evaluation Metrics
  6. Analyst’s Take
  7. About Andrew Brust

1. Summary

The runaway growth of data in the enterprise puts organizations in a tough spot. To help them manage, manipulate, query, and present a unified view of the data estate, organizations must turn to data virtualization platforms that help consolidate disparate data sources logically, without forcing data to be physically moved or transformed. This Key Criteria report explores the workings of solutions in this sector and provides guidance around key solution criteria and characteristics to drive better decision making.

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