Gartner Research

Hype Cycle for Data Management, 2006

Published: 06 July 2006

ID: G00140057

Analyst(s): Mark Beyer , John Radcliffe , Andreas Bitterer , Ted Friedman , Raymond Paquet , Bill Gassman , Mike Blechar , Toby Bell , Rita E. Knox , Andrew White , Debra Logan , Donald Feinberg , Karen M. Shegda , David Newman , Carolyn DiCenzo

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
  • What You Need to Know
  • The Hype Cycle
  • The Priority Matrix
  • On the Rise
    • Model-Driven Data Services
    • Open-Source Data Integration Tools
    • Hosted Data Integration and Data Quality
    • Database Archiving
    • Enterprise Information Management
    • Data Service Architectures
    • Master Data Management
    • Metadata Repositories
    • Data Enrichment
    • OSS DBMS for Data Warehousing
  • At the Peak
    • OSS DBMS for Mission-Critical Applications
    • XQuery
    • Content Integration
    • Data Integration Tools Convergence
    • Data Profiling
  • Sliding Into the Trough
    • Data Warehouse Appliances
    • Data Federation/EII
    • OSS DBMS for Simple Applications
    • Linux as a DBMS Platform
    • Real-Time Data Integration
  • Climbing the Slope
    • Data Cleansing and Matching
    • XML-Enabled Database Management Systems
    • Mobile and Portable Device DBMS
  • Entering the Plateau
    • ETL Tools
  • Appendices
    • Previous Iteration of the Hype Cycle
    • Hype Cycle Phases, Benefit Ratings and Maturity Levels

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