Critical Capabilities for Data Science and Machine Learning Platforms


Published: 04 April 2018 ID: G00335261

Analyst(s): | | | | |

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Summary

The functions and features of data science and machine learning platforms are evolving quickly to keep pace with a highly innovative and hyped space. This research helps data and analytics leaders evaluate 17 data science and machine learning platforms across 15 critical capabilities.

Table of Contents

  • What You Need to Know
  • Analysis
    • Critical Capabilities Use-Case Graphics
    • Vendors
      • Alteryx
      • Anaconda
      • Angoss
      • Databricks
      • Dataiku
      • Domino Data Lab
      • H2O.ai
      • IBM
      • KNIME
      • MathWorks
      • Microsoft
      • RapidMiner
      • SAP
      • SAS (Enterprise Miner)
      • SAS (Visual Analytics Suite)
      • Teradata
      • TIBCO Software
    • Context
    • Product/Service Class Definition
    • Critical Capabilities Definition
      • Data Access
      • Data Preparation
      • Data Exploration and Visualization
      • Automation
      • User Interface
      • Machine Learning
      • Other Advanced Analytics
      • Flexibility and Openness
      • Performance and Scalability
      • Delivery
      • Platform and Project Management
      • Model Management
      • Precanned Solutions
      • Collaboration
      • Coherence
    • Use Cases
      • Business Exploration
      • Advanced Prototyping
      • Production Refinement
    • Vendors Added and Dropped
      • Added
      • Dropped
  • Inclusion Criteria
    • Gate 1
    • Gate 2
    • Gate 3
    • Critical Capabilities Rating
  • Appendix
  • Gartner Recommended Reading
© 2018 Gartner, Inc. and/or its Affiliates. All Rights Reserved. Reproduction and distribution of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartners research may discuss legal issues related to the information technology business, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice.

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