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This How-To Guide is based on a series of interviews Ovum conducted with end-user organizations and independent practitioners implementing analytics and business intelligence in a pan-enterprise fashion. We point out common pain-points, best practices, and key technologies that can help enterprises looking to transform their analytic environment from siloed islands of information to connected ecosystems.


  • Analytics exists across enterprises in different forms and flavors, tailored to audiences and use cases, but with very little integration and collaboration – like islands of information and insight.
  • Most enterprises want to develop an orchestrated, connected ecosystem of analytics that draws from not only a rigid data warehouse but also data virtualization, NewSQL/analytic approaches, and data lakes.
  • To get from islands to ecosystems, organizations need to examine current and desired analytical states, find the gaps in existing solutions, select technology based on use cases, assess costs and benefits, and collaborate on an ongoing basis.

Features and Benefits

  • Focuses on maturity issues, lessons learned, and barriers to be overcome for successful analytics adoption.
  • Provides practical guidance gleaned from enterprise interviews.

Key questions answered

  • What components comprise enterprise analytics?
  • What are the major data unification methods and technologies?
  • What do organizations need to keep in mind when executing a transformational analytics program?

Table of contents


  • Catalyst
  • Ovum view
  • Key messages


  • Start with assessments
  • Think about data hygiene before, alongside, and after analytics
  • Identify stakeholders, assess IT and business culture to get buy-in
  • Remember, product + services = solution

Where we are: Analytics in all shapes and forms for different audiences and use cases

  • What comprises enterprise analytics?
  • Why do we need so many types of analytics?
  • What's wrong with one centralized, IT-driven platform?

Target: Orchestrated, connected ecosystem of analytics

  • Beyond the data warehouse as the unification point for all data
  • Mapping a logical structure for a connected ecosystem

How to get from islands to ecosystems

  • Examine your current and desired state of data/analytics
  • Highlight fault lines in existing analytics solutions/processes
  • Zero in on use case–based technology selection
  • Find the costs and benefits of deploying new systems
  • Deploy, assess results, and remain flexible


  • Methodology
  • Further reading
  • Author

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