Technical professionals focused on security and data are struggling to find strategic and tactical approaches to secure the big data and advanced analytics pipeline. We break down the pipeline into upstream, midstream and downstream and provide guidance on where security must go.
- 1. What Is the Big Data and Advanced Analytics Pipeline?
- 2. Security Issues and Controls in the Big Data and Advanced Analytics Pipeline
- 2.1. Data Polymorphism
- 2.2. Unknown Data Relations and Dark Data
- 2.3. Poisoning Training Data or Tampering With Data, Feature Representations or ML Algorithms
- 2.4. Infrastructure Attacks
- 2.5. Data Theft
- 2.6. Data Linkage and Other Inference Attacks
- 2.7. Emerging Insights Not Covered by Data Governance Policies
- 2.8. Compliance Requirements and External Expectations
- 3. Strengths
- 4. Weaknesses
- 1. Constantly Leverage Standardized Access to the BAAP as Part of All Solutions
- 2. Decide Between Buy and Build Strategies
- 3. Minimize Dark Data by Capturing Metadata
- 4. Empower Different Teams to Contribute to Different Aspects of the Pipeline
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