data-governance-checkup 0.1.0

A library for data governance and compliance

Data Governance Library

The Data Governance Library is a Python package designed to help organizations maintain data compliance, security, and governance standards. With features tailored to address common regulatory frameworks like GDPR, HIPAA, ISO 27001, and more, this library provides tools for automated compliance checks, metadata management, data lineage tracking, and role-based access control auditing.

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Features

1. Automated Compliance Checks

   • Support for frameworks like GDPR, HIPAA, ISO 27001, and CCPA.
   • Customizable rules for new compliance standards.

2. Data Lineage Tracking

   • Monitor data flow and identify its origin, transformation, and destination.

3. Role-Based Access Control (RBAC) Auditing

   • Ensure that data access policies are adhered to.

4. Metadata Management and Cataloging

   • Store, manage, and query metadata associated with your datasets.

5. Data Masking and Anonymization

   • Protect sensitive data with masking and anonymization techniques.

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Installation

Install the library via pip:

pip install data-governance-library

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Usage

Example: Running Compliance Checks

from data_governance.compliance.gdpr import GDPRCompliance
from data_governance.compliance.hipaa import HIPAACompliance
from data_governance.compliance.iso27001 import ISO27001Compliance

# Sample data to validate
data = {
    "personal_data": "John Doe",
    "PII_encrypted": False,
    "PHI": "Medical Record",
    "PHI_encrypted": False,
    "backup_enabled": False,
    "sensitive_data_access": [{"user": "alice", "logged": False}],
}

# Run GDPR compliance checks
gdpr_violations = GDPRCompliance.check(data)
print("GDPR Violations:", gdpr_violations)

# Run HIPAA compliance checks
hipaa_violations = HIPAACompliance.check(data)
print("HIPAA Violations:", hipaa_violations)

# Run ISO 27001 compliance checks
iso_violations = ISO27001Compliance.check(data)
print("ISO 27001 Violations:", iso_violations)

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Data Lineage Tracking

from data_governance.lineage.lineage import DataLineageTracker

tracker = DataLineageTracker()
tracker.add_record("dataset1", "source1")
tracker.add_record("dataset2", "dataset1")

# Get lineage for a specific dataset
lineage = tracker.get_lineage("dataset2")
print("Lineage:", lineage)

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Metadata Management

from data_governance.metadata.metadata_manager import MetadataManager

manager = MetadataManager()
manager.add_metadata("dataset1", {"owner": "Alice", "description": "Sales data"})
metadata = manager.get_metadata("dataset1")
print("Metadata:", metadata)

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Role-Based Access Control (RBAC) Auditing

from data_governance.rbac.rbac_audit import RBACAuditor

auditor = RBACAuditor()
auditor.add_role("Alice", ["read", "write"])
violations = auditor.audit_access("Alice", "delete")
print("RBAC Violations:", violations)

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Data Masking and Anonymization

from data_governance.masking.anonymizer import DataAnonymizer

anonymizer = DataAnonymizer()
masked_data = anonymizer.mask("123-45-6789", "SSN")
print("Masked Data:", masked_data)

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Contributing

Contributions are welcome! Please submit pull requests or open issues for any enhancements, bugs, or additional compliance frameworks you'd like to see.

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License

This project is licensed under the MIT License. See the LICENSE file for more details.

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Roadmap

1. Add support for more compliance standards (e.g., SOC 2, PCI DSS).
2. Build visualization dashboards for compliance status.
3. Integrate with real-time data pipelines for live compliance checks.

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Contact

For questions or support, please contact pratik.lahudkar@gmail or open an issue on the GitHub repository.