Hype Cycle for Data Management, 2011

G00213386

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Summary

Data management technologies and practices are evolving fast to address the explosion in the volume, variety and velocity of data, and the convergence of data management disciplines. Use this Hype Cycle to understand and seize opportunities arising from established and emerging capabilities.

Table of Contents

  • Analysis
    • What You Need to Know
    • The Hype Cycle
    • The Priority Matrix
    • Off The Hype Cycle
    • On the Rise
      • Open-Source Data Quality Tools
      • Information Semantic Services
      • "Big Data" and Extreme Information Processing and Management
      • Enterprise Information Management Programs
      • Data Integration Platform as a Service
      • Data Integration Tools and Data Quality Tools Convergence
      • Information Capabilities Framework
    • At the Peak
      • Enterprise Taxonomy and Ontology Management
      • In-Memory Data Grids
      • noSQL Database Management Systems
      • Complex-Event Processing
      • Data Services
      • Data Stewardship Applications
      • Database Platform as a Service
      • Enterprisewide Metadata Repositories
      • Data Quality Software as a Service
      • Cross-Platform Structured Data Archiving
      • Entity Resolution and Analysis
      • In-Memory Database Management Systems
      • Open-Source Data Integration Tools
      • Data Stewardship
    • Sliding Into the Trough
      • MapReduce
      • Master Data Management
      • Data Integration Tool Suites
      • Database Software as a Service
      • Content Integration and Migration
      • Data Profiling
      • Open-Source Database Management Systems
    • Climbing the Slope
      • Data Federation/Virtualization
      • Column-Store Database Management Systems
      • Data Quality Tools
      • Database Appliances
    • Appendixes
      • Hype Cycle Phases, Benefit Ratings and Maturity Levels
  • Recommended Reading
© 2011 Gartner, Inc. and/or its Affiliates. All Rights Reserved. Reproduction and distribution of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartners research may discuss legal issues related to the information technology business, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice.

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