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This Ovum Decision Matrix provides an overview of the self-service data prep market and is intended to assist the enterprise in the vendor short-listing process by evaluating the leading vendors, their platforms, and their positioning.


  • In the market at large, there is a trend of self-service data prep "platformization," whereby data prep functionality is increasingly being baked into larger data management and analytics platforms rather than being offered as a standalone tool.
  • Machine learning is becoming a major differentiator between self-service data prep products. "Smart" guided functionality in self-service data prep tools, driven by machine learning, is expanding the potential user base to increasingly nontechnical business users.
  • Information governance functionality is increasing in importance for self-service data prep environments, particularly with regulations such as GDPR going into effect. Many self-service data prep products are embedding data catalogs; the enterprise demands the ability to audit and see lineage for transformations.

Features and Benefits

  • Evaluates all aspects of the key players in the self-service data prep market: their features, their platforms, and their positioning.
  • Compares self-service data prep products on measures of technology, execution, and market impact.
  • Assesses the historical factors and trends that led to the development of today's various self-service data prep platforms and architectural approaches.
  • Analyzes the current trends in self-service data prep functionality and development, and evaluates the current role of self-service data prep in the analytics and data science ecosystem.
  • Assesses the strengths, weaknesses, opportunities, and threats of each respective self-service data prep vendor.

Key questions answered

  • Which vendors are the leaders, challengers, and followers in the self-service data prep market?
  • What are the categories of features and functionality that define a modern self-service data prep offering?
  • What features are most closely matched across vendor offerings, and which features are most differentiating?
  • What variations in self-service data prep architecture exist, and how are these platform variations suited to various enterprise IT environments?
  • What are the strengths, weaknesses, opportunities, and threats facing each respective vendor in the self-service data prep market?

Table of contents


  • Catalyst
  • Ovum view
  • Key findings

Vendor solution selection

  • Inclusion criteria
  • Exclusion criteria
  • Methodology
  • Ovum ratings
  • Ovum Interactive Decision Matrix

Market and solution analysis

  • Ovum Decision Matrix: Self-Service Data Prep, 2018–19
  • Market leaders: ClearStory Data, Datameer, Trifacta, and Unifi
  • Market challengers: Alteryx, Datawatch, and Oracle
  • Market followers: IBM

Market leaders

  • Market leaders: technology
  • Market leaders: execution
  • Market leaders: market impact

Vendor analysis

  • Alteryx Designer, version 11.8 (Ovum recommendation: Challenger)
  • ClearStory Data, version 2.7 (Ovum recommendation: Leader)
  • Datameer Enterprise, version 7.1 (Ovum recommendation: Leader)
  • Datawatch Monarch, version 14.3 (Ovum recommendation: Challenger)
  • IBM Data Refinery (Ovum recommendation: Follower)
  • Oracle Analytics Cloud, version 17.4.5 (Ovum recommendation: Challenger)
  • Trifacta Wrangler, version 4.2 (Ovum recommendation: Leader)
  • Unifi Data Platform, version 2.6 (Ovum recommendation: Leader)


  • Methodology
  • Further reading
  • Author

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