Gartner Research

Adopt Data Virtualization to Improve Agility and Bimodal Traits in Your Aging Data Integration

Published: 14 July 2017

ID: G00327618

Analyst(s): Mei Selvage, Ehtisham Zaidi

Summary

Data virtualization is a key component in a modern data integration tool portfolio, and can support both analytical and operational use cases. This research will help data and analytics leaders adopt data virtualization for the right use cases, maximize its ROI and minimize risks.

Table Of Contents
  • Key Challenges

Introduction

Analysis

  • Investigate the Technical and Business Benefits of Complementing Your Existing Data Integration Architecture With Data Virtualization to Enable Diverse and Distributed Data Access
    • Technical and Business Benefits
  • Adopt Data Virtualization for Use Cases Beyond Traditional Analytics by Exploring Operational and Emerging Use Cases
    • Traditional Analytical Use Cases
    • Traditional Operational Use Cases
    • Emerging Use Cases
  • Start Implementing Data Virtualization by Identifying Use Cases Requiring Faster Data Access, Transient Schemas and High Flexibility
    • Data Virtualization
    • Bulk/Batch (ETL or ELT)
    • Data Replication
    • Messaging
  • Appendix

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