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Introduction

This report investigates what capabilities define enterprise-grade self-service analytics solutions.

Highlights

  • To be classed as enterprise grade, self-service analytics tools have to enable better data management and access control, stay easy to use despite growing underlying technical complexity, and stay easy to deploy no matter where the data sits.

Features and Benefits

  • Identifies the hurdles faced by self-service analytics solutions in enabling enterprise-wide, data-driven decision-making.
  • Identifies what capabilities define enterprise-grade self-service analytics solutions.

Key questions answered

  • What obstacles hinder data-driven decision-making across enterprises?
  • What key capabilities define enterprise-grade self-service analytics solutions?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

Aiming to make enterprises' everyday decisions data driven

  • Addressing the issues of traditional BI
  • New IT environment, new hurdles

Enterprise-grade self-service analytics solutions tackle the challenges of the new data landscape

  • Accessing trustworthy data means built-in data governance and preparation
  • Getting closer to a human UI
  • Embedded analytics and hybrid platforms are not just buzzwords anymore

Without a strong data governance framework, self-service analytics solutions cannot be truly enterprise-grade

  • Technology alone will not lead to data-driven decision-making
  • Putting users first
  • Smooth processes to unlock the full potential of self-service analytics

Appendix

  • Methodology
  • Further reading
  • Author

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