Hype Cycle for Big Data, 2013

Archived Published: 31 July 2013 ID: G00252431


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Big data is a phenomenon of data usage closely linked to the "Information Age." This Hype Cycle will help enterprise information strategists separate differing approaches and technology solutions in order to find a new way of working with huge amounts of information that will be the new norm.

Table of Contents

  • Analysis
    • What You Need to Know
    • The Hype Cycle
    • The Priority Matrix
    • Off The Hype Cycle
    • On the Rise
      • Big Data Analytics for Customer Service
      • Information Valuation and Infonomics
      • Operational Intelligence Platforms
      • Quantified Self
      • Graph Databases
      • Big Data Analytics for E-Commerce
      • High-Performance Message Infrastructure
      • Data Science
      • Search-Based Data Discovery Tools
      • Intent-Driven Customer Systems
      • Table-Style Database Management Services
    • At the Peak
      • Information Capabilities Framework
      • Information Semantic Services
      • Video Search
      • Hadoop SQL Interfaces
      • Internet of Things
      • Logical Data Warehouse
      • Document Store Database Management Systems
      • Complex-Event Processing
      • Context-Enriched Services
      • Content Analytics
      • Dynamic Data Masking
      • Key-Value Database Management Systems
      • Cloud-Based Grid Computing
      • In-Memory Database Management Systems
    • Sliding Into the Trough
      • Social Analytics
      • Entity Resolution and Analysis
      • Sales Analytics
      • Telematics
      • Hadoop Distributions
      • In-Memory Data Grids
      • Cloud Parallel Processing
      • Database Software as a Service (dbSaaS)
      • Cloud Computing
      • Text Analytics
      • In-Memory Analytics
    • Climbing the Slope
      • Intelligent Electronic Devices
      • Social Media Monitors
    • Entering the Plateau
      • Speech Recognition
      • Predictive Analytics
    • Appendixes
      • Hype Cycle Phases, Benefit Ratings and Maturity Levels
  • Recommended Reading
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