Contextual Intelligence (Data + AI)

Understanding the context of data is imperative for meaningful data management and effective data security efforts. Data context includes attributes like data sensitivity, usage, access entitlements, configurations, privileges, risks, and regulatory context, to name a few. Contextual intelligence around data enables organizations to piece together all the siloed data points for complete, comprehensive data understanding. By leveraging these insights, organizations can effectively strategize and prioritize their security endeavors, remediate risks promptly, and ensure timely compliance with regulatory frameworks.

However, gaining context of data is fairly challenging as organizational data is isolated across various tools and departments. Disparate data makes it difficult for data management, security, privacy, compliance, and business operations teams to make sense of the information available across an organization for informed business decisions. Not only does it hinder analytics teams from leveraging the data effectively for analytics or BI, but it also impedes effective remediation.

Similarly, when data breaches occur, it becomes critical for teams to accurately discover the impacted data, the affected identities, and the regulatory implications. All these insights rely heavily on contextual intelligence.

DSPM overcomes this mounting challenge by leveraging a centralized knowledge graph. This capability pulls all the data context together to give a comprehensive relationship of data, AI, risks, policies, and controls. Data teams can think of it as a Google search for data and AI. The knowledge can correlate various metadata to give granular details down to the table or column level. This powerful capability makes it possible for teams to solve complex data problems via a unified source of truth.