Gartner Research

Upgrade the Enterprise Data Warehouse Architecture With Hadoop

Published: 09 April 2015

ID: G00275430

Analyst(s): Svetlana Sicular

Summary

Hadoop is becoming an accepted component of an enterprise information architecture and infrastructure. This research explains to information management professionals the strengths and weaknesses of Hadoop in complementing an enterprise data warehouse, taking a step toward building the LDW.

Table Of Contents

Analysis

  • Upgrade the EDW With Hadoop to Build the LDW
  • Drivers for Implementing Hadoop
  • Bimodality of the EDW and Hadoop
    • The EDW as Mode 1: Marathon
    • Hadoop as Mode 2: Sprint
  • How Hadoop Complements the EDW
  • Implications of the New Architecture on Your Current EDW
    • Your Data Warehouse Still Has an Important Role
    • Hadoop Affects Design Principles of Operational Data Stores and Data Marts
  • Strengths
  • Weaknesses

Guidance

  • Develop Governance for Bimodal IT
  • Evolve Your Architecture on a Use-Case-by-Use-Case Basis
  • Introduce a Data Lake If Necessary, but First, Define What It Is
  • Make Choices for the Gray Areas
  • Pace Your Hadoop Adoption
  • Grow Your Internal Skills

The Details

  • Why Do Organizations Use Hadoop With the EDW?
    • Cost Reduction
    • A More Comprehensive Data Management Analytic Solution
    • Very Large Files
    • Flexibility
  • How Can Hadoop Complement the EDW?
    • Typical Hadoop Components for Complementing a DW
    • Data Integration Frameworks
    • ETL Is the Most Prominent Pattern for Integrating Hadoop and the EDW
    • Data Ingest Methods
    • Propagating Analytical Models, Data and Metadata Is the Greatest Challenge
    • What to Offload
    • Query Capability Is the Most Common Requirement
    • An Archive Is Live and Active

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