This skill helps organizations achieve robust data governance, mitigate compliance risks.

Discover Data Sources
Map Constraints and Classify Data
Generate Governance Plan

Security

Efficiently integrate data, ensure quality, and trace lineage for AI apps.

The AI Data Constraint and Governance Mapper automatically maps data constraints and generates a governance plan for AI applications. It helps data engineers overcome struggles with integrating new datasets and ensuring data quality.

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$170.00, paid once. Later versions included. Non refundable digital download.

What the skill checks for you

Data engineers often make assumptions about data quality and compliance. The AI Data Constraint and Governance Mapper verifies these assumptions by performing automated checks, reducing manual effort and risk.

What is usually assumed	What the skill checks
All data sources consumed by the AI application are known and documented.	The skill verifies that all identified data sources are accounted for in the constraint map.
Sensitive data fields are correctly identified and protected.	The skill checks that sensitive data fields are correctly classified and protected according to policies.
Data retention policies are consistently applied across all data stores.	The skill confirms data retention policies are applied consistently across relevant data stores.
Data quality meets the required thresholds for AI model performance.	The skill verifies data quality metrics meet defined thresholds (e.g., completeness, uniqueness).

Questions Data Engineers Ask

1
Our existing data catalog tools already provide some data lineage.
What it looks at: The skill analyzes discovered data sources to identify data schemas, trace data lineage, and understand usage patterns, providing detailed documentation.
2
Manually mapping data constraints is time-consuming but we have dedicated resources.
What it looks at: The skill automatically maps data constraints and generates a governance plan for AI applications, reducing the need for extensive manual effort.
3
We are concerned about giving an AI agent access to our code repositories and infrastructure configurations.
What it looks at: The skill has read-only access to AI application code repositories, infrastructure configurations, and data storage systems, ensuring no modifications are made.
4
How can I be sure the generated governance plan is accurate and complete?
What it looks at: The skill compares existing data access controls and pipeline configurations with the proposed data governance plan, identifying discrepancies and proposing remediation.
5
What if my data sources are not easily discoverable or accessible?
What it looks at: If a data source is inaccessible, it reports the access error and marks that source's constraints as unverified.

What you get from the skill

The AI Data Constraint and Governance Mapper provides actionable insights and plans to streamline your data governance efforts.

Data Constraint Map: A detailed map outlining data quality requirements, privacy classifications, and compliance obligations for all discovered data sources.
Data Governance Plan: A draft plan specifying access controls for support ticket data, a 2-year retention policy for sentiment analysis results, and an audit trail for all data access.
Discrepancy Report: A report detailing discrepancies and potential compliance risks, for example, flagging that current S3 bucket policies allow broader access than required for the sentiment model.

These values are an example. Your output will reflect your specific AI application and data environment.

From manual effort to automated governance

Instead of Manually identifying all data sources and their schemas across complex architectures.
With the skill The skill inspects code repositories and infrastructure configurations to identify all data sources and map their schemas automatically.
Instead of Struggling to ensure consistent data quality across integrated datasets.
With the skill The skill profiles data for completeness, consistency, and validity by running automated data profiling and validation checks.
Instead of Spending significant manual effort on data auditing and policy enforcement.
With the skill The skill generates a comprehensive data governance plan draft and compares it against existing controls, identifying gaps for efficient enforcement.
Instead of Dealing with outdated data constraint maps and governance plans due to changes.
With the skill The skill establishes automated monitoring on code repositories, data sources, and regulatory databases to detect changes and prompt updates.

How the skill works securely

Runs on your secure environment
The skill runs through a Model Context Protocol (MCP) server, meaning the agent communicates with a live external system within your secure environment. All processing is done locally or within your secure environment.
Read-only access for safety
This skill requires read-only access to sensitive assets like code repositories, infrastructure configurations, and data storage systems. It does not modify any data, code, or infrastructure configurations.
Focus on identification, not modification
The skill only flags discrepancies and suggests remediation steps. It performs data classification and identifies compliance risks by processing potentially sensitive data, but it never makes unintended changes.

Questions and answers

Our existing data catalog tools already provide some data lineage.

While existing tools may offer some lineage, this skill goes further by inspecting code repositories and infrastructure configurations to discover all data sources consumed by the AI application. It then identifies data schemas, lineage, and usage patterns to produce a detailed data constraint map and governance plan. This provides a comprehensive, AI-specific view.

Manually mapping data constraints is time-consuming but we have dedicated resources.

The AI Data Constraint and Governance Mapper automates the discovery of data sources, identification of schemas, lineage, and usage patterns. It then generates a detailed data constraint map and a draft data governance plan. This significantly reduces the manual effort and time required, allowing your dedicated resources to focus on higher-value tasks.

We are concerned about giving an AI agent access to our code repositories and infrastructure configurations.

This skill operates with read-only access to your AI application code repositories, infrastructure configurations, and data storage systems. It inspects these assets to identify issues and propose solutions but will never modify your data, code, or infrastructure directly. All suggested changes require your explicit approval and manual implementation.

How can I be sure the generated governance plan is accurate and complete?

The skill generates a comprehensive draft data governance plan, including proposed access controls, data retention policies, and audit trails. It then compares this plan against your existing data handling practices, flagging any discrepancies. If a regulatory requirement is ambiguous, it highlights the ambiguity and requests clarification, ensuring accuracy and completeness.

How does the skill handle changes in regulations or my application?

The skill establishes automated monitoring on code repositories, data sources, and relevant regulatory databases. Upon detecting changes, it re-evaluates the data constraint map and governance plan, flags new risks, and suggests necessary adjustments to maintain continuous compliance and data quality.

Achieve robust data governance for your AI applications.

The AI Data Constraint and Governance Mapper helps data engineers efficiently integrate new datasets, ensure consistent data quality, and maintain clear data lineage across complex AI architectures. It automates the mapping of data constraints and generation of governance plans.