There’s little doubt that modern organizations value data as paramount to drive their business decisions and market competitiveness. However, poor data quality continues to be their Achilles heel.
Every year, data-driven organizations continue to incur high costs due to poor data quality. IBM estimates that the average cost impact of poor data for businesses is around $9.7 million. While 74% of companies want to be data-driven, only 29% are successful at converting data insights into actions.
Essentially, these are some of the costs of inefficient data governance, which drives poor decision-making based on low-quality data. At the same time, excessive data governance can often complicate and delay actions.
Another organizational concern is data security and proper access control. As data ecosystems grow larger and more complex, organizations can no longer rely on “traditional” data authentication and authorization practices to keep their valuable data secure and accessible to the right personnel.
As part of digital transformation, organizations are switching to data entitlement and access as a means to improve data governance, security, and compliance. Here’s a comprehensive guide to a scalable data entitlement framework – that can address organizational concerns about data governance.
In this blog, we discuss data entitlement and access – and why it is critical for data-driven organizations.
What is data entitlement?
According to Gartner’s definition, data entitlement technology manages finely-grained access-based entitlements to execute IT policies to access organizational data, systems, and devices. Data entitlement management includes tasks like enforcing, revoking, resolving, and administering IT privileges.
Data entitlement goes much beyond the “traditional” mechanism of access control. By enforcing finely-grained policies on data access and governance, data entitlement frameworks account for both of the following considerations:
- Which user is trying to access the data?
- Under what context are they accessing the data – including time, location, and device?
Why should data entitlement matter? Here are some reasons:
- It provides precise control over which user can access specific data within a larger dataset.
- It guarantees regulatory compliance by making sensitive data accessible to users with special permissions.
- It improves data governance and auditing by providing overall transparency over who can access data and for what purpose.
How organizations can implement data entitlement and access
Depending on their data requirements, organizations need a customized approach to implementing data entitlement and access. Here are some of the most effective practices:
- The first step is to classify the existing data based on its sensitivity and regulatory requirements.
- Next, implement a role-based data entitlement framework to assign role-based permissions to individual users or groups.
- Implement attribute-based data policies that are based on:
- The user’s attributes like job role and business function
- Other attributes like the time and location of data access
- Execute dynamic entitlement that is based on assigning access permissions in real-time conditions.
- Perform regular audits and reviews of the data entitlement policies in line with changing business and compliance requirements.
Among other recommendations, organizations can invest in AI-powered data entitlement tools and frameworks to ensure finely-grained control over their data. For example, Generative AI-powered LLMs like Google’s Vertex AI can secure data environments with capabilities like:
- Data privacy and governance
- Data security and compliance
- Operational sustainability
- Responsible AI