Gartner Research

Forecast: Data Science in Vertical Industries, Worldwide, 2016-2022

Published: 22 June 2018

ID: G00338670

Analyst(s): Susan Cournoyer , Katell Thielemann , Steve Crawford , Venecia Liu , Derry Finkeldey , Rajesh Kandaswamy , Michael Dornan , Moutusi Sau , Hanna Karki , Molly Beams , Anurag Gupta , Kenneth Brant

Summary

Vendors of data science software (data science platforms, self-service data preparation and stream analytics) are rethinking their go-to-market strategies. Technology product managers should prioritize the vertical industry use cases that best match their organizations' product strategy.

Table Of Contents

Forecast Data

Analysis

  • Overview
    • Banking and Securities
    • Communications, Media and Services
    • Education
    • Government
    • Healthcare
    • Insurance
    • Manufacturing and Natural Resources
    • Retail
    • Transportation
    • Utilities
    • Wholesale Trade
    • Cross-Industry Use Cases

Assumptions

  • Total Addressable Market
  • Data and Analytics Requirements
  • Business Initiatives
  • Purchase Behavior
  • Use-Case Complexity
  • Pricing
  • Technology Innovation
  • User Expansion
  • Functional Expansion

Methodology

  • Data Science Platforms
  • Self-Service Data Preparation
  • Stream Analytics Platform Software
  • Market Model
    • Macroeconomics
    • Firmographics
    • Data and Analytics Requirements
    • Business Initiatives (How Technology Is Implemented to Meet Business Needs)
    • Purchase Behavior
    • Functional Expansion (Complexity of Implementation Over Time)
    • User Expansion (Pervasiveness of the Technology in the Enterprise)
    • Technology Innovation (Supply Side)
    • Pricing

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