A Guide to Data Entitlements & Access
At Scale

How organizations can develop a framework for secure and auditable data platforms

Inefficient data governance is a challenge when implementing data-driven projects. Excessive – or too little – data governance and controls often complicate projects, resulting in delays and cost escalations. This guide provides a common framework for data entitlements and access – along with a reference architecture for Google Cloud Platform (GCP).

Did you know?

Between 60-73% of enterprise data remains unused for analytics.
The global market for data governance tools is expected to be valued at $5.25 billion by 2026.
By downloading this guide, you will learn more about:
  • Common framework patterns in physical data storage and security, data classification and cataloging, and user and application persona.
  • Implementing and scaling data entitlements and security for Google Cloud.
  • Controlling access to machine learning and LLM models.
  • Securing and preparing environments for Generative AI.

We can help you “walk” your path to data entitlement and access.


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