Gartner Research

How TSPs Can Overcome Buying Hurdles for Data Science and Machine Learning Solutions

Published: 06 June 2018

ID: G00362694

Analyst(s): Alys Woodward , Eric Hunter

Summary

Data science and machine learning solutions are increasingly dependent on open-source, public cloud, and enterprise consumer data assets. Software technology product marketing leaders must address these new market driver impacts or face delayed/failed deal closures.

Table Of Contents
  • Key Challenges

Introduction

  • Legal Drivers
  • People Drivers
  • Technology Drivers

Analysis

  • Equip Sales Teams in Managing Evolving Roles and Responsibilities
  • Directly Address Business and Technology Stakeholder Interests
    • Technology/Software Engineering Buyer Team Stakeholders
    • Business/Data Science Buyer Team Stakeholders
  • Prioritize Data Sensitivity and Security Dependency Awareness
  • Proactively Equip Technology Governance Stakeholders
  • Account for Increased Public Cloud Management Processes
  • Provide Proactive Guidance for Funding Model Decisions

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