Modern Approaches to Data Access Management: Balancing Data Access and Data Security
Data access management (DAM) seeks to balance two critical needs. It must protect the organization’s data while also enabling greater access to capture its value. This is a complex task since today’s environments span multiple data formats, locations, and processing platforms. Constantly changing privacy regulations and exploding demand for data create new challenges that render previous approaches to data access management ineffective.
Until recently, DAM required a trade-off between data access and data protection. More data access meant less data protection; more stringent protection meant less data access. This zero-sum game does not work for today’s complex global data landscape.
The modern approach to DAM provides both greater data access and better data protection through centrally managed and universally enforced data access policies. Data access management solutions dynamically evaluate every data request against applicable access policies at runtime to determine what data the requester can see. They apply surgical access rules that specify how sensitive data can be displayed—e.g., masked, encrypted, or not shown at all. They enable data governance teams to centrally manage data access policies and equip data system administrators with no-code/low-code tools to configure automated enforcement.
There are two primary ways vendors approach policy enforcement. The first approach is through generating code that the source data system executes to enforce policies. The second is a proxy data engine that preprocesses data from a data source to apply policy access rules.