Data Warehouse Architecture Best Practices and Guiding Principles

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Summary

Gartner inquiries confirm that specific data architecture principles in the data warehouse add years to its life. Data architects and warehouse managers should implement data warehouse architectures using these best practices.

Table of Contents

  • Analysis
    • 1.0 What Are the SLA Issues in the Data Warehouse?
      • 1.1 Performance Issues
      • 1.2 Data Latency and Data "Freshness"
      • 1.3 Data Warehouse Availability
      • 1.4 Mixed Workload Usage Requirements
      • 1.5 Data Warehouses Participate in a Larger Information Infrastructure
    • 2.0 Understanding the Six "-Ables"
    • 3.0 "Permanent" Demands on the Data Architecture
    • 4.0 Bringing the SLA and Data Architecture Together
  • Recommended Reading
© 2009 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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