Gartner Research

Information Lifecycle Management and Data Management: The Chicken or the Egg?

Published: 08 July 2009

ID: G00203766

Analyst(s): Noreen Kendle

Summary

Data has grown exponentially within organizations. Its volume has become extremely costly, in terms of usability, performance, and quality--which negatively impacts organizations' bottom lines. Organizations are turning to information lifecycle management (ILM) as a way to control the data overload and more effectively manage their information. But the success of ILM depends on a solid enterprise data management foundation. In this overview, Burton Group Analyst Noreen Kendle describes the synergy between ILM and enterprise data management and discusses how ILM and enterprise data management together can help an organization more effectively manage data at a lower cost.

Table Of Contents

Summary of Findings

Analysis

  • A Data Perspective
    • Data
    • Data Growth
    • Data Retention
    • Data Overload
  • Information Lifecycle Management
    • Drivers for ILM
    • DLM and ILM
    • Data Archiving
    • ILM Principles
    • Data Retention Policy
    • ILM Strategy
    • ILM Process
  • Enterprise Data Management and ILM
    • Data as a Business Asset
    • Enterprise Data Management Foundation for ILM
    • Data Ownership
    • Data Standards
    • Data Modeling and Design
    • Enterprise Metadata
    • Data/Information Classification and Valuation
    • Data Lineage and Relationship Tracking
    • Data Quality Management
    • Data Change Management
  • Recommendations
    • Learn the Principles of Enterprise Data Management
    • Establish a Solid Enterprise Data Management Practice
    • Secure Executive Support
    • Use a Business-Driven ILM Strategy
    • All Data Is Not Equal; Treat It Accordingly
    • Do Not Take a “Storage Only” ILM Approach
    • Don't Use a Data Warehouse as an Archival Solution
    • Don't Take the “Delete Everything” or “Save Everything” Stance
    • Don't Assume Deletion—Verify Deletion
    • Don't Assume Archived Information Is Restorable

The Details

  • Moore's Law
  • Data Growth Statistics

Conclusion

Notes

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