The Goal: Reducing data risks and compliance challenges is a priority for most C-suite executives, since it impedes innovation. Failure to comply with regulations is costly, requires expensive legal defenses, and can be brand tarnishing.
The Requirements: There are an array of complex data governance and compliance mazes to which executives and business managers must adhere. From protecting personal data and privacy to ensuring that sensitive business data is not exposed or used in unauthorized ways, business teams need to remain compliant when innovating with data sets combined from multiple owners.
The Challenge: Data ownership is complex. Individuals and organizations can lay claim to the same data and stewards of data owned by others remain responsible for any misuse or exfiltration that may occur under their watch. For business teams, this means sensitive data must be available in combination for analytics, but cannot be exposed directly to analysts in violation of the owner’s corporate policies and regulations.
The Problems: Conventional systems can be configured to allow users to expose or change data owned by another party. If data Owner A shares raw data with Owner B, using a conventional system, then Owner B can use the combined data sets in violation of Owner A’s rules. Legal agreements cannot be relied upon to prevent data misuse. Most data sharing projects get stuck as a result. Reliance on 3rd party services do not provide the capability for self-service analytics, and do not provide the data quality and transparency required to ensure the analytics are generating accurate results.
The Myngl Concordance Solution: Secure Analytics Containers use Zero-Trust microservices to decentralize security, governance and compliance controls to data owners. Access to shared data requires explicit “Need-to-Know” authorization from each data owner and analytics use commingled data without exposing it. Our point of view is simple: “With Data, Trust No One.”