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This primer for analytics-driven enterprises and vendors helps define and map the analytics market. It has been written to help vendors understand their role and to position themselves within the landscape relative to traditional peers, new entrants, and prospective partners. It is also for users/practitioners of analytics, to help them understand the market in its diversity.


  • Large enterprise adoption and the active participation of mega-vendors validates the importance of this market. It will likely consume the world of curated analytics, or be subsumed by it; coexistence is imperative.
  • “Where do I sit in the value chain?” is one of the most pressing questions for vendors, prompting vendors of all sorts and sizes to actively seek information validating their relevance, strategy, and opportunity in the self-service analytics market.

Features and Benefits

  • Assesses the market landscape for self-service analytics.
  • Details the key enterprise adoption drivers for self-service analytics.

Key questions answered

  • Who are the key vendors in this market and how do they stack up against each other?
  • What are the key differentiators of market vendors?

Table of contents


  • Catalyst
  • Key messages
  • Ovum view

Recommendations for vendors

  • Go to market with strategies that reflect your strengths

Recommendations for enterprises

  • How do I select among market players?

Defining and exploring self-service analytics

  • Self-service analytics is the consumer persona of enterprise analytics
  • The self-service analytics technology super-stack
  • Enterprise adoption drivers for self-service analytics solutions

Market landscape and participants

  • Self-service analytics providers come in many sizes and flavors
  • A market moving towards some consolidation
  • Self-service analytics market outlook
  • Self-service analytics value chain
  • Vendor landscape
  • Ecosystem interdependencies and influences

Self-service analytics: Where is it heading next?

  • Self-service is the beginning of the evolutionary endpoint for BI
  • Big picture versus exact picture: We don't believe in the "two camps" theory

Vendor profiles

  • IBM: Bringing cognitive to self-service
  • Oracle: Embedded self-service on functional/industry clouds
  • Microsoft: The most ubiquitous self-service analytics vendor
  • SAS: Self-service for a broad sweep of users, novice to expert
  • SAP: Self-service paradigm across a massive portfolio
  • Tableau: The pioneer of self-service of analytics, going strong
  • Qlik: Visual analytics for the enterprise
  • Chartio: Agile analytics solution growing quickly past its start-up status
  • Logi: Visualization, analytics, and embedding
  • MicroStrategy: Version 10 is all about enterprise data discovery
  • Domo: Facebook meets self-service analytics
  • Yellowfin: Collaborative dashboarding and reporting
  • GoodData: Cloud analytics geared to "data monetization"
  • Birst: Networked analytics with self-service
  • Amazon QuickSight: "Aha moment" – native analytics for Amazon data
  • Salesforce: Ramping up on the adoption curve
  • Platfora: Big Data Discovery on Apache Hadoop and Spark
  • Datameer: Data discovery for Hadoop, end to end
  • Looker Data Sciences: Analytics on live data


  • Methodology
  • Further reading
  • Author

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