How to Build Your Own Big Data Security Analytics Capability

Archived Published: 01 June 2015 ID: G00276099


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Select enterprises have embarked on the journey toward building their own security analytics capabilities, sometimes using big data technologies and approaches. This assessment summarizes some of the lessons and describes the merits of such an undertaking.

Table of Contents

  • Analysis
    • Security Analytics and Big Data Security Analytics
      • Security Analytics
      • Big Data Use for Security
      • Build, Buy, Partner
    • Why Build? Motivation for Exploring Big Data Analytics for Security
      • Common Conditions for Building Your Own Security Analytics Technology
    • Build Your Own: Key Build Success Factors and Prerequisites
      • The Analytics Mindset
      • The Big Three of Required Skills
      • Lessons From Other Big Data Successes
    • How to Build the Analytics Capability
      • Two Analytics Approaches
      • "Analytics First, Big Second" Thinking
      • Secure Your Warehouse
    • Operationally Successful Big Data Use Cases
      • Big Data Scenario 1: Outgrowing Log Management
      • Big Data Scenario 2: Too Much Variety
      • Big Data Scenario 3: Big Search to Big Data
      • Big Data Scenario 4: Big Narrow Data
    • SIEM and Big Data: Working Together
    • Top Challenges to Wider Adoption
    • Near-Future Directions
    • Strengths
    • Weaknesses
  • Guidance
  • The Details
    • Big Data for Security: Example Implementation
  • Gartner Recommended Reading
© 2015 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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