Enterprise Intelligence, Business Analytics and Decisioning

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Megha Kumar

Research VP, Analytics and AI



Enterprise Intelligence, Business Analytics and Decisioning targets both strategies and technologies that allow for data-driven decision-making. This research service covers the trends and dynamics driving the uptake of business analytics, decisioning, and enterprise performance management within organizations. It provides insights into the processes and investments being undertaken by organizations when it comes to analyzing data, generating and sharing insights, and building a data-driven culture. It covers the impact of cloud, automation, and AI (including generative AI [GenAI]) on these technologies. The research can also be leveraged by organizations when it comes to setting an overall data and analytics strategy that encompasses people, processes, and technology via the enterprise intelligence scorecard and framework.


Markets and Subjects Analyzed


  • Business Intelligence and Analytics
  • Enterprise Performance Management
  • Decision Intelligence
  • Enterprise Intelligence Adoption
  • AI and Generative AI for Decision-Making

Core Research


  • Business Intelligence and Analytics Trends and Forecast
  • Adoption of Embedded Analytics and Self-Service Analytics
  • Enterprise Performance Management Trends and Forecast
  • IDC MarketScape: Business Intelligence, Enterprise Performance Management, and Decision Intelligence Software
  • Overall Data and Analytics Forecast
  • Impact of AI (Including GenAI) on Business Intelligence and Analytics
  • Best Practices Around Building a Data-Driven Culture with Enterprise Intelligence Maturity

In addition to the insight provided in this service, IDC may conduct research on specific topics or emerging market segments via research offerings that require additional IDC funding and client investment.


Key Questions Answered


  1. What are the drivers and challenges around business intelligence and analytics adoption?
  2. How are organizations embracing embedded analytics?
  3. How is AI impacting analytics? What are the GenAI use cases impacting this space?
  4. What are the trends and dynamics impacting enterprise performance management?
  5. How should enterprises rethink their investments to enable superior enterprise intelligence?
  6. What metrics can be used to measure enterprise intelligence?
  7. What are the priorities of personas such as chief data officers, CFOs, and chief AI officers as it relates to analytics, business intelligence, and decision-making?
  8. What are the user behaviors and trends in the overall analytics market?

Companies Covered