A library for data governance and compliance
Project description
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.
Features
-
Automated Compliance Checks
- Support for frameworks like GDPR, HIPAA, ISO 27001, and CCPA.
- Customizable rules for new compliance standards.
-
Data Lineage Tracking
- Monitor data flow and identify its origin, transformation, and destination.
-
Role-Based Access Control (RBAC) Auditing
- Ensure that data access policies are adhered to.
-
Metadata Management and Cataloging
- Store, manage, and query metadata associated with your datasets.
-
Data Masking and Anonymization
- Protect sensitive data with masking and anonymization techniques.
Installation
Install the library via pip:
pip install data_governance_checkup
Usage
Example: Running Compliance Checks
from data_governance_checkup.compliance.gdpr import GDPRCompliance
from data_governance_checkup.compliance.hipaa import HIPAACompliance
from data_governance_checkup.compliance.iso27001 import ISO27001Compliance
from data_governance_checkup.compliance.ccpa import CCPACompliance
# Sample data
data = {
"personal_data": "John Doe",
"PHI": "Medical Record",
"PHI_encrypted": False,
"backup_enabled": False,
"sensitive_data_access": [{"user": "alice", "logged": False}],
"data_sold": True,
"consumer_consent": False,
}
# Run compliance checks
gdpr_violations = GDPRCompliance.check(data)
hipaa_violations = HIPAACompliance.check(data)
iso_violations = ISO27001Compliance.check(data)
ccpa_violations = CCPACompliance.check(data)
# Print results
print("GDPR Violations:", gdpr_violations)
print("HIPAA Violations:", hipaa_violations)
print("ISO 27001 Violations:", iso_violations)
print("CCPA Violations:", ccpa_violations)
Data Lineage Tracking
from data_governance_checkup.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)
Metadata Management
from data_governance_checkup.metadata.metadata_manager import MetadataManager
manager = MetadataManager()
manager.add_metadata("dataset1", {"owner": "Alice", "description": "Sales data"})
metadata = manager.get_metadata("dataset1")
print("Metadata:", metadata)
Role-Based Access Control (RBAC) Auditing
from data_governance_checkup.rbac.rbac_audit import RBACAuditor
auditor = RBACAuditor()
auditor.add_role("Alice", ["read", "write"])
violations = auditor.audit_access("Alice", "delete")
print("RBAC Violations:", violations)
Data Masking and Anonymization
from data_governance_checkup.masking.anonymizer import DataAnonymizer
anonymizer = DataAnonymizer()
masked_data = anonymizer.mask("123-45-6789", "SSN")
print("Masked Data:", masked_data)
Contributing
Contributions are welcome! Please submit pull requests or open issues for any enhancements, bugs, or additional compliance frameworks you'd like to see.
License
This project is licensed under the MIT License. See the LICENSE file for more details.
Roadmap
- Add support for more compliance standards (e.g., SOC 2, PCI DSS).
- Build visualization dashboards for compliance status.
- Integrate with real-time data pipelines for live compliance checks.
Contact
For questions or support, please contact pratik.lahudkar@gmail or open an issue on the GitHub repository.
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