Hype Cycle for Data Management, 2006

G00140057

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Summary

Technologies and best practices for data management continue to evolve rapidly. The Gartner Hype Cycle for Data Management can help organizations understand the relative maturity of these technologies and best practices, the benefits of adoption, and key factors for successful deployment.

Table of Contents

  • Analysis
    • 1.0 What You Need to Know
    • 2.0 The Hype Cycle
    • 3.0 The Priority Matrix
    • 4.0 On the Rise
      • 4.1 Model-Driven Data Services
      • 4.2 Open-Source Data Integration Tools
      • 4.3 Hosted Data Integration and Data Quality
      • 4.4 Database Archiving
      • 4.5 Enterprise Information Management
      • 4.6 Data Service Architectures
      • 4.7 Master Data Management
      • 4.8 Metadata Repositories
      • 4.9 Data Enrichment
      • 4.10 OSS DBMS for Data Warehousing
    • 5.0 At the Peak
      • 5.1 OSS DBMS for Mission-Critical Applications
      • 5.2 XQuery
      • 5.3 Content Integration
      • 5.4 Data Integration Tools Convergence
      • 5.5 Data Profiling
    • 6.0 Sliding Into the Trough
      • 6.1 Data Warehouse Appliances
      • 6.2 Data Federation/EII
      • 6.3 OSS DBMS for Simple Applications
      • 6.4 Linux as a DBMS Platform
      • 6.5 Real-Time Data Integration
    • 7.0 Climbing the Slope
      • 7.1 Data Cleansing and Matching
      • 7.2 XML-Enabled Database Management Systems
      • 7.3 Mobile and Portable Device DBMS
    • 8.0 Entering the Plateau
      • 8.1 ETL Tools
    • 9.0 Appendices
      • 9.1 Previous Iteration of the Hype Cycle
      • 9.2 Hype Cycle Phases, Benefit Ratings and Maturity Levels
  • Recommended Reading
© 2006 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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