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Introduction

The capabilities of analytics solutions continue to evolve at a rapid pace, yet the market for these solutions is playing catch-up. This brief provides Ovum's view of four key trends that will help shape analytics over the coming year, helping you explore the themes shaping the market, discover opportunities, and prepare for change.

Highlights

  • The user audience for analytics is constantly growing, enabled by the adoption of new flavors of analytics to suit a broader variety of users. The challenge is a long-standing one: silos. Ovum expects the beginnings of convergence between the three key areas of analytics within the enterprise: corporate, self-service, and big data.

Features and Benefits

  • Explore the trends in 2017 that Ovum expects will shape enterprises' adoption and use of analytics.
  • Prepare for the coming change as analytics capabilities start to converge across the enterprise.

Key questions answered

  • What are the key themes in analytics influencing enterprises' adoption and use of analytics and supporting technologies?
  • How can enterprises spread the benefits of data-driven insight across the broadest user audience?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

Business trends and technology enablers

  • Trends in analytics

Convergence of corporate, self-service, and big data analytics is coming

  • Consolidation of analytics in the enterprise is inevitable and technology is catching up
  • As enterprises benefit from converging capabilities, vendors must prepare for a battle of frenemies

Machine learning and automation is the enterprise reality of AI science fiction

  • Automation is for the mundaneness of data management and the complexity of advanced analytics
  • Vendors will incorporate AI into every solution
  • A market for algorithms will emerge

Distributed analytics will divide and conquer the IoT data challenge

  • Data management and analytics will spread throughout the IoT
  • Upgrading data architectures must balance new capabilities with existing investments

Analytics services providers will talk exclusively in terms of business outcomes because the clients have changed

  • The power to sign checks for services moves ever further from IT
  • Enterprises are hungry for data and analytics services; they just do not know which ones

Appendix

  • Methodology
  • Author

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