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Computational Governance Platform

The Computational Governance Platform Module automates the data governance of Witboost users, throughout the entire data component lifecycle.

Enforce governance policies as code and automate their implementation, creating non-by-passable rules.



Automate and enforce governance throughout the whole process.


Increase overall quality standards and reduce compliance risks.


Gain full visibility on policy results and drill down to a specific resource if necessary.


Create and maintain a centralized repository of human and machine-readable computational policies.

Policy Register

Define and manage the lifecycle of computational policies end to end.

View and mange all computational policies in the Policy Register.

Manage computational policy roll-out and deprecation.

Check computational policy status and versions, as well as issues.

Learn about computational policies in this deep-dive white paper.

Policy Editor

Drill down to specific policies from the Policy Register.

Edit policies and test their compliance before deploying.

Instantly know about non-compliance issues before deploying.

Policy Validation

Provide a real time and global picture about the level of compliance of all the data initiatives in your organization.

Drill down to specific data components and spot patterns with the use of filters.

Instantly view and interact with data owners for urgent compliance needs.

Drill down to multiple data components that are non-compliant or have multiple issues.

View policy score and compare with data initiative templates that have built-in best practices.

Policy Back Testing

Test a policy before releasing it. Run it across the entire Policy Register to detect any issues.

Understand impacts, drawbacks, and dependencies.

Instant view of areas with issues, enabling to fix only non-compliance issues without the need to go through all of them.

Filter policies for specific data initiatives that require a certain type of policy.

Module Use Case: Data Governance Shift Left on Data Lake

  • Metadata as code: Templates can embed whatever kind of metadata, business information, build and deploy information

  • You build it, you Govern it: The team in charge to develop the use case is forced to provide also metadata, documentation and security in order to pass computational policies

  • No guidelines: Computational policies are code and enforced automatically, so that no-one need to verify manually anything. Also it provides transparency ensuring that all the users are going through them and not by-passing them

  • Context aware: Policies are coming with documentation and decision records to explain to the community why a specific policy is needed
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