Data Governance and Data Quality

1. Data Governance

  • The process of managing data availability, usability, integrity, and security to meet organizational policies and compliance requirements.
  • Goal: Ensure data is reliable, secure, and used effectively.

Key Components:

  1. Policies: Rules for managing data (e.g., access, usage).
  2. Data Ownership: Assign roles like Data Owners (accountable) and Data Stewards (manage daily data tasks).
  3. Compliance: Follow regulations like GDPR, HIPAA.
  4. Data Security: Protect data from breaches and unauthorized access.

Benefits of Data Governance:

  • Improves decision-making.
  • Ensures compliance with legal standards.
  • Minimizes risks of data misuse.

2. Data Quality

  • The measure of how accurate, complete, consistent, and reliable data is for its intended purpose.
  • Goal: Provide trustworthy and high-quality data for decision-making.

Dimensions of Data Quality:

  1. Accuracy: Data must reflect real-world facts.
  2. Completeness: No missing values.
  3. Consistency: Data is uniform across systems.
  4. Timeliness: Data is updated and available on time.
  5. Validity: Data conforms to defined formats or standards.

3. Difference Between Data Governance and Data Quality

AspectData GovernanceData Quality
FocusPolicies, processes, complianceData accuracy, reliability
ScopeHigh-level managementTechnical quality checks
OutcomeSecure and controlled data useHigh-quality, usable data

4. Steps to Implement Data Governance

  1. Define goals and policies.
  2. Assign roles (e.g., Data Owners, Stewards).
  3. Create a data governance framework.
  4. Monitor compliance and refine policies.

5. Tools for Data Governance and Quality

  • Collibra: Data governance and stewardship.
  • Informatica: Data quality and governance.
  • Talend: Data integration and quality.

6. Challenges in Data Governance and Quality

  • Lack of stakeholder buy-in.
  • Difficulty in monitoring compliance.
  • Handling large volumes of data.

How to Overcome:

  • Automate data quality checks.
  • Regular audits and reviews.
  • Train employees on governance policies.

Quick Mnemonics for Revision

Data Governance Goals: “PODS”

  • P: Policies.
  • O: Ownership.
  • D: Data Security.
  • S: Standards and Compliance.

Data Quality Dimensions: “ACT CV”

  • A: Accuracy.
  • C: Completeness.
  • T: Timeliness.
  • C: Consistency.
  • V: Validity.