DataViz Explorer

🔑 Free Exclusive Career Checklist:
Data Governance Specialist

This checklist outlines the initial steps to establish policies, roles, and standards that ensure data quality, security, and compliance across an organization.

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1. Regulatory & Policy Fundamentals

Step	Action Item	Status
1.1	Core Regulations: Understand and explain the key provisions of at least two major data regulations (GDPR, HIPAA, CCPA) and how they relate to data handling.
1.2	Data Roles & Ownership: Define the roles of the Data Steward, Data Owner, and Data Custodian and understand the RACI matrix for data assets.
1.3	Policy Drafting: Draft a simple data retention policy that defines how long specific data categories (e.g., customer PII) must be stored.
1.4	Data Risk Assessment: Practice classifying data by sensitivity (e.g., Public, Internal, Confidential) and determining its potential business impact if breached.
1.5	Ethics in Data: Research and be able to explain two key ethical issues in data (e.g., algorithmic bias, privacy violation) and how governance can mitigate them.

2. Data Quality & Metadata Management

Step	Action Item	Status
2.1	Data Quality Dimensions: Learn the six key dimensions of data quality (Accuracy, Completeness, Consistency, Timeliness, Validity, Uniqueness).
2.2	Metadata Creation: Create a business glossary with clear definitions, data formats, and ownership for 10 core business terms (e.g., Customer, Transaction ID).
2.3	Data Profiling: Use a tool (like Python/Pandas or a data quality tool) to profile a dataset and identify null values, outliers, and format inconsistencies.
2.4	Master Data Management (MDM): Understand the concept of a “Golden Record” and the challenges of creating a single, consistent view of core entities (like Customer or Product).
2.5	Governance Technology: Research the features of a common Data Catalog/Governance platform (e.g., Collibra, Informatica, Atlan).

3. Professional Development & Portfolio

Step	Action Item	Status
3.1	Create a Governance Project: Document a project where you defined governance for a new dataset, including policy, metadata, and quality rules.
3.2	Stakeholder Communication: Practice explaining a complex governance policy (e.g., PII anonymization) to a skeptical business manager, focusing on risk reduction.
3.3	Learn Industry Frameworks: Study the **DAMA-DMBOK** (Data Management Body of Knowledge) wheel and its 11 knowledge areas.
3.4	Update Resume Keywords: Use terms like Data Governance, Data Quality, Metadata Management, Regulatory Compliance (GDPR/HIPAA), and Data Stewardship.
3.5	Data Lineage Tooling: Understand how data lineage tools help audit compliance and track the source of data quality issues.