Gartner Research

Hype Cycle for Enterprise Information Management, 2018

Published: 31 July 2018

ID: G00340487

Analyst(s): Andrew White , Saul Judah

Summary

Data and analytics leaders can find it challenging to consistently deliver business value through their data and analytics investments. Enterprise information management can help to align, link and make the most of people, processes, data and technologies.

Table Of Contents

Analysis

  • What You Need to Know
  • The Hype Cycle
  • The Priority Matrix
  • Off the Hype Cycle
  • On the Rise
    • Information Products
    • Adaptive Data and Analytics Governance
    • DataOps
    • Artificial General Intelligence
    • Data Literacy
    • Trust-Based Data and Analytics Governance
    • Data for Good
    • Data Storytelling
    • Continuous Intelligence
    • Human-in-the-Loop Crowdsourcing
    • Algorithmic Business
    • Infonomics
    • Self-Service Data & Analytics
  • At the Peak
    • Data Hub Strategy
    • Citizen Data Science
    • Data Classification
    • Decision Management
    • Digital Ethics
    • File Analysis
    • Graph Analytics
    • Prescriptive Analytics
    • Data as a Service
    • Analytics Governance
    • Data Catalog
    • Data Engineering
    • Enterprise Metadata Management
    • Machine Learning
    • Open Data
    • Business Capability Modeling
    • Data and Analytics Governance
  • Sliding Into the Trough
    • Enterprise Information Management Programs
    • Data Lakes
    • Information Architecture
    • Predictive Analytics
    • Information Stewardship
    • Master Data Management
    • Logical Data Warehouse
  • Climbing the Slope
    • Data and Analytics Services
    • SaaS Archiving of Messaging Data
    • Enterprise Information Archiving
    • Content Migration
  • Appendixes
    • Hype Cycle Phases, Benefit Ratings and Maturity Levels

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