Gartner Research

Hadoop and MapReduce: Big Data Analytics

Published: 14 January 2011


Big data analytics and the Apache Hadoop open source project are rapidly emerging as the preferred solution to address business and technology trends that are disrupting traditional data management and processing. Enterprises can gain a competitive advantage by being early adopters of big data analytics.

Included in Full Research

  • Disruptive Changes on Traditional Data Processing
    • Increasing Data Volumes
    • Increasing Data Complexity
    • Increasing Analysis Complexity
    • Changing Analysis Model
    • Increased Acceptance of Open Source Software
    • Increasing Availability of Cost-Effective Compute and Storage
  • Data-Processing Pipeline
  • Structured Data
  • Big Data Analytics Classification
    • Speed of Decision Making
    • Processing Complexity
    • Transactional Data Volumes
    • Data Structure
    • Flexibility of Processing/Analysis
    • Throughput
    • Summary
  • Big Data Analysis Technology
    • Data Management Frameworks
    • Processing Frameworks
    • Development Frameworks
    • Modeling Frameworks
    • Management Frameworks
    • Integration Frameworks
    • Open Source Hadoop
    • Hadoop in the Cloud
    • Hadoop Hardware
    • Hadoop Futures
    • Hadoop Use Cases
  • Big Data Analysis as a Competitive Advantage
  • Strengths
  • Weaknesses
  • Adopt Big Data Analytics and the Hadoop Open Source Project to Meet the Challenges of the Changing Business and Technology Landscape
  • Adopt a Packaged Hadoop Distribution to Reduce Technical Risk and Increase the Speed of Implementation
  • Be Selective About Which Hadoop Projects to Implement
  • Use Hadoop in the Cloud for Proof of Concept
  • The Big Data Analytics Initiative Should Be a Joint Project Involving Both IT and Business
  • Enterprises Should Not Delay Implementation Just Because of the Technical Nature of Big Data Analytics
  • Adapt Existing Architectural Principles to the New Technology


Marcus Collins

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