Gartner Research

Gartner Magic Quadrant for Data Science and Machine Learning Platforms

Summary

Expert data scientists and other professionals working in data science roles require capabilities to source data, build models and operationalize machine learning insights. Significant vendor growth, product development and myriad competing visions reflect a healthy market that is maturing rapidly.

Published: 11 February 2020

ID: G00385005

Analyst(s): Peter Krensky , Pieter den Hamer, Erick Brethenoux , Jim Hare , Carlie Idoine , Alexander Linden , Svetlana Sicular , Farhan Choudhary

Table Of Contents

Market Definition/Description

Magic Quadrant

  • Vendor Strengths and Cautions
    • Altair
    • Alteryx
    • Anaconda
    • Databricks
    • Dataiku
    • DataRobot
    • Domino
    • Google
    • H2O.ai
    • IBM
    • KNIME
    • MathWorks
    • Microsoft
    • RapidMiner
    • SAS
    • TIBCO Software
  • Vendors Added and Dropped
    • Added
    • Dropped

Inclusion and Exclusion Criteria

  • Inclusion Criterion No. 1: Data Science and Machine Learning Platform Offering
  • Inclusion Criterion No. 2: Revenue and Number of Paying Customers
  • Inclusion Criterion No. 3: Customer Counts
  • Inclusion Criterion No. 4: Product Capability Scoring
  • Exclusion Criteria
  • Honorable Mentions

Evaluation Criteria

  • Ability to Execute
  • Completeness of Vision
  • Quadrant Descriptions
    • Leaders
    • Challengers
    • Visionaries
    • Niche Players

Context

Market Overview

Gartner Recommended Reading

  • Ability to Execute
  • Completeness of Vision

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