Compliance cannot be optional

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In theory, this sounds ideal: each team is responsible for the safety and accuracy of its data. But it depends on being able to move data management from a centralized IT function into the hands of product owners. Then empowering those teams to analyze, understand, and use the data without the need for endless technical support and intervention. And at the same time, ensuring impeccable compliance with internal governance standards and external regulations.

And herein lies the rub. when responsibility is decentralized, and it cannot be bypassed if a new project needs to be implemented. It must be mandatory.

Data mesh needs fences
In reality, expecting employees to remember to follow data bangladesh mobile database and compliance guidelines is unfair and unrealistic. Compliance should be implemented without annoying users and should be an integral part of the project implementation process. A computational governance platform (CGP) that allows control and monitoring of all aspects of data computing can, as strange as it may sound, simultaneously establish the necessary standards as “guardrails” and speed up time to market.

Sitting on top of an organization’s existing data management and toolset, CGP ensures that each project follows pre-defined rules for quality, compliance, security, and architecture. Highly customizable standards can be set at a global or local level, as needed. Importantly, projects can only go into production if all required criteria are met. There is no way to override or ignore the rules.

CGP can expand capabilities
While this may seem limiting, there are many benefits to working in a standardized way. Process-optimizing, intelligent, automated templates help data scientists quickly initiate new projects and find the data they need. The platform can manage the deployment of data products, checking their compliance and taking care of resource provisioning, freeing teams from having to manage the technical aspects of infrastructure (cloud or on-premises) while simultaneously validating data products before they go into production. These automated templates make life easier for users, significantly reducing delivery times and speeding time to market.