Active metadata management is a set of capabilities that enables continuous access and processing of metadata that support ongoing analysis over a different spectrum of maturity, use cases and vendor solutions. Active metadata outputs range from design recommendations based upon execution results and reports of runtime steps through, and indicators of, business outcomes achieved. The resulting recommendations from those analytics are issued as design inputs to humans or system-level instructions that are expected to have a response.
Data security posture management (DSPM) provides visibility as to where sensitive data is, who has access to that data, how it has been used, and what the security posture of the data stored or application is. It does that by assessing the current state of data security, identifying and classifying potential risks and vulnerabilities, implementing security controls to mitigate these risks, and regularly monitoring and updating the security posture to ensure it remains effective. As a result, it enables businesses in maintaining the confidentiality, integrity, and availability of sensitive data. The typical users of DSPM include Information Technology (IT) departments, security teams, compliance teams, and executive leadership.
Legislators motivated by aggressive digitalization and increased consumer concern about the handling of personal data — especially when it comes to AI workloads and data-sharing practices — have passed laws governing consumer privacy rights.1,2,3,4 These rights have become part of consumers’ basic expectations when engaging with commercial organizations or government entities. At the heart of the SRR automation market are three key capabilities: Discovery of existing information held on individuals, and continuous monitoring for changes to data stores and new systems that are being onboarded. Maintenance of the capacity to act on that information should the data subject request modification, deletion or restriction of processing. Tracking of request workflows and holding of detailed records to gauge effectiveness and demonstrate compliance. Organizations face great challenges in sifting through structured and unstructured data stores — whether on-premises, in the cloud, or with partners and subprocessors. In addition to the discovery and retrieval requirement, organizations must redact personal data that is associated with other individuals to ensure they are not violating one user’s rights in order to respond to another. For those reasons, request fulfillment must follow a repeatable and scalable process in order to remain manageable and efficient.