Gartner Research

Securing the Data and Advanced Analytics Pipeline

Published: 27 January 2020

Summary

Security and risk management technical professionals are struggling to find strategic and tactical approaches to secure the data and advanced analytics pipeline. We break down the pipeline into upstream, midstream and downstream and provide guidance on where security must go.

Included in Full Research

  • What Is the Data and Advanced Analytics Pipeline?
  • Eight Key Security Considerations in the DAAP Pipeline
    • 1. Data Polymorphism
    • 2. Unknown Data Relations and Dark Data
    • 3. Poisoning Training Data or Tampering With Data, Feature Representations or Analytical Models
    • 4. Infrastructure Attacks
    • 5. Data Theft or Unintended Disclosure
    • 6. Data Linkage and Other Inference Attacks
    • 7. Emerging Insights Not Covered by Data Governance Policies
    • 8. Compliance Requirements and External Expectations
  • Strengths
  • Weaknesses
  • Constantly Leverage Standardized Access to the DAAP as Part of All Solutions
    • Build, Potentially Based on Components You Can Buy
  • Minimize Dark Data by Capturing Metadata
  • Empower Different Teams to Contribute to Different Aspects of the Pipeline

Analysts:

Joerg Fritsch

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