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Introduction

As a self-service BI visualization tool that natively takes advantage of Spark computing, Zoomdata's long-term edge will be in its ability to distribute and scale query processing to get around memory or caching bottlenecks.

Highlights

  • Zoomdata provides one of the first big data end-user visualization tools designed around the emerging, high-performance Spark in-memory computing framework.

Features and Benefits

  • Analyzes how Zoomdata is at the beginning of an increasingly competitive wave of self-service BI analytics tools that will inevitably leverage Spark in-memory processing.
  • Explains Zoomdata’s differentiator: combining visualization with a back-end stream processing engine that makes the tool extremely scalable across multi-node clusters and enables end users to integrate multiple heterogeneous back-end data platforms.

Key questions answered

  • How does Zoomdata differentiate from self-service BI/analytics providers Tableau and Qlik?
  • How does Zoomdata harness the emerging Spark compute engine to deliver self-service analytics to big data?

Table of contents

Summary

  • Catalyst
  • Key messages
  • Ovum view

Recommendations for enterprises

  • Why put Zoomdata on your radar?

Highlights

  • Background
  • Current position

Data sheet

  • Key facts

Appendix

  • On the Radar
  • Further reading
  • Author

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