Data Governance Best Practices¶

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Best practices for data governance in Cloud Scale Analytics.

Overview¶

Effective data governance ensures:

• Data quality and consistency
• Regulatory compliance
• Data security and privacy
• Clear data ownership and accountability

For detailed guidance, see: Full Data Governance Guide

Key Practices¶

1. Data Classification¶

# Azure Purview classification scan
from azure.purview.scanning import PurviewScanningClient

client = PurviewScanningClient(
    endpoint="https://purview.purview.azure.com",
    credential=credential
)

# Configure classification rules
scan_ruleset = {
    "name": "pii-scan",
    "kind": "AdlsGen2",
    "properties": {
        "scanRulesetName": "pii-ruleset",
        "collection": {"referenceName": "data-collection"}
    }
}

2. Data Lineage¶

flowchart LR
    A[Source Systems] --> B[Bronze Layer]
    B --> C[Silver Layer]
    C --> D[Gold Layer]
    D --> E[Analytics]
    D --> F[ML Models]
    D --> G[Reports]

3. Access Control¶

4. Data Quality Rules¶

-- Data quality checks
CREATE TABLE data_quality_rules (
    rule_id INT,
    table_name VARCHAR(100),
    column_name VARCHAR(100),
    rule_type VARCHAR(50),
    rule_expression VARCHAR(500),
    threshold DECIMAL(5,2)
);

-- Example rules
INSERT INTO data_quality_rules VALUES
(1, 'customers', 'email', 'NOT_NULL', 'email IS NOT NULL', 99.9),
(2, 'customers', 'email', 'FORMAT', 'email LIKE ''%@%.%''', 99.0),
(3, 'orders', 'amount', 'RANGE', 'amount BETWEEN 0 AND 1000000', 99.9);

Governance Framework¶

Data Stewardship¶

• Assign data stewards per domain
• Define data ownership policies
• Establish data quality SLAs
• Create data dictionaries

Compliance¶

• GDPR data subject rights
• Data retention policies
• Audit logging requirements
• Cross-border data transfer rules

Related Documentation¶

• Azure Purview Integration
• Data Lineage

Last Updated: January 2025