Portfolioβ€ΊData Analyticsβ€ΊData Governance & Quality
Topic

Data Governance & Quality

Ensure data is trustworthy, compliant, and well-documented. Tests data dictionaries, quality checks, and privacy compliance.

Data dictionariesData qualityPOPIA/GDPR complianceData documentation

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Topic Execution Guide

Data Governance & Quality Auditing (POPIA / GDPR Compliance)

Data governance ensures data assets are accurate, complete, accessible, and compliant with privacy laws like POPIA and GDPR. Analysts demonstrate enterprise readiness by conducting data quality audits, tracking data lineage, and anonymizing PII data.

1. Corporate Data Governance Policy Spec

Governance framework detailing data ownership roles, data classification tiers, and quality SLAs.

2. Data Quality Audit Script & Rule Engine

Automated script testing data completeness, uniqueness, consistency, and validity across core tables.

3. PII Anonymization & Hashing Verification Log

Log verifying hashing and masking of customer PII data (emails, phone numbers) before analytical export.

Frequently Asked Questions (Data Governance & Quality)

What are the 6 core dimensions of data quality?

Completeness, Accuracy, Consistency, Timeliness, Uniqueness, and Validity.

How do you anonymize Personally Identifiable Information (PII) for analytics?

PII is anonymized using SHA-256 cryptographic hashing, tokenization, or generalization (e.g. replacing exact birth dates with age brackets).

What is data lineage?

Data lineage tracks the complete lifecycle of data, mapping its origin, transformation steps, and downstream dependencies across systems.

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