Critical Capabilities for Data Science Platforms

Archived Published: 07 June 2017 ID: G00326671

Analyst(s): | | | | |

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The data science market is being transformed by disruptive technologies and high expectations for artificial intelligence. Data and analytics leaders should closely monitor market conditions for 2017, which dictate new critical capabilities and use-case scenarios for data science platforms.

Table of Contents

  • What You Need to Know
  • Analysis
    • Critical Capabilities Use-Case Graphics
    • Vendors
      • Alpine Data
      • Alteryx
      • Angoss
      • Dataiku
      • Domino Data Lab
      • FICO
      • IBM
      • KNIME
      • MathWorks
      • Microsoft
      • Quest
      • RapidMiner
      • SAP
      • SAS (EM)
      • SAS (VAS)
      • Teradata
    • 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
      • Production Refinement
      • Business Exploration
      • Advanced Prototyping
      • Added
      • Dropped
  • Inclusion Criteria
    • Gate 1
    • Gate 2
    • Gate 3
    • Critical Capabilities Rating
  • Gartner Recommended Reading
© 2017 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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