Data Governance

Question 1

What is data governance?

Answer 1

A framework of policies, processes, and standards that ensures data is accurate, secure, and available for business use.

Data governance is essential for maintaining data integrity and compliance.

Question 2

Why is data governance important?

Answer 2

• Ensures data quality
• Ensures compliance
• Ensures security
• Promotes proper usage across the organization

Effective data governance helps organizations manage their data assets responsibly.

Question 3

What are the main goals of data governance?

Answer 3

• Ensure data accuracy and quality
• Protect sensitive data
• Ensure compliance with regulations (like GDPR, HIPAA)
• Promote consistent data usage across the organization

These goals help organizations manage their data effectively.

Question 4

What are the key components of data governance?

Answer 4

• Data policies and standards
• Data stewardship
• Data quality management
• Metadata management
• Compliance and auditing

These components work together to create a robust data governance framework.

Question 5

What is a data steward?

Answer 5

A person responsible for managing and maintaining data quality and compliance within a business domain.

Data stewards play a crucial role in ensuring data governance is effective.

Question 6

What is data quality in data governance?

Answer 6

Refers to accuracy, completeness, consistency, timeliness, and validity of data.

High data quality is essential for effective decision-making.

Question 7

How do you measure data quality?

Answer 7

• Accuracy (correct values)
• Completeness (no missing data)
• Consistency (uniform data across systems)
• Timeliness (updated and current)

These metrics help assess the overall quality of data.

Question 8

What is master data governance (MDG)?

Answer 8

Manages critical business entities like customers, suppliers, products to ensure a single source of truth.

MDG is vital for maintaining consistent and accurate master data.

Question 9

Difference between data governance and data management?

Answer 9

• Data governance: Policies and standards
• Data management: Day-to-day operations of collecting, storing, and maintaining data

Understanding this distinction is key for effective data strategy.

Question 10

What is metadata management?

Answer 10

Managing data about data, such as its origin, format, and usage rules.

Metadata management is crucial for understanding and utilizing data effectively.

Question 11

How does data governance improve data security?

Answer 11

By defining who can access data, how it’s used, and ensuring encryption and compliance.

Strong data governance frameworks enhance overall data security.

Question 12

What is GDPR and its relevance to data governance?

Answer 12

GDPR is a European regulation protecting personal data.

Data governance ensures compliance with GDPR by controlling access and usage of personal data.

Question 13

What are data access controls?

Answer 13

Policies defining who can view or modify data.

Access controls are essential for maintaining data security.

Question 14

What is data lineage?

Answer 14

Tracks where data comes from, how it is transformed, and where it is used.

Understanding data lineage is important for data governance and compliance.

Question 15

How do you ensure compliance in data governance?

Answer 15

• Through audits
• Policies
• Automated monitoring
• Reporting

Compliance is a critical aspect of effective data governance.

Question 16

What is a data governance policy?

Answer 16

A formal document defining how data is created, stored, shared, and protected.

Policies guide the implementation of data governance.

Question 17

Who are the key roles in data governance?

Answer 17

• Data Owner: Responsible for data accuracy
• Data Steward: Maintains quality
• Data Custodian: Manages technical aspects
• Data Governance Council: Approves policies

These roles ensure effective data governance implementation.

Question 18

What is data standardization?

Answer 18

Applying uniform formats and definitions across data sets.

Standardization helps in maintaining data consistency.

Question 19

What is data classification?

Answer 19

Categorizing data based on sensitivity or importance (e.g., public, confidential, restricted).

Data classification is crucial for data protection and compliance.

Question 20

What is the difference between a data owner and data steward?

Answer 20

• Data Owner: Defines policies and approves usage
• Data Steward: Implements policies and ensures data quality

Both roles are essential for effective data governance.

Question 21

How would you implement data governance in an organization?

Answer 21

• Define goals and policies
• Assign roles (owners, stewards, custodians)
• Implement data quality and metadata management
• Monitor compliance
• Continuously improve

A structured approach is necessary for successful implementation.

Question 22

How would you handle poor data quality in a critical dataset?

Answer 22

• Identify issues (duplicates, missing, inconsistent data)
• Cleanse and standardize data
• Implement validation rules and monitoring

Addressing data quality issues is vital for maintaining data integrity.

Question 23

How does data governance support analytics?

Answer 23

By ensuring accurate, reliable, and consistent data, analytics can provide meaningful insights.

Good data governance is foundational for effective analytics.

Question 24

Give an example of a data governance tool.

Answer 24

• Collibra: Data governance and cataloging
• Informatica Axon: Data governance framework
• SAP MDG: Master data governance

These tools help organizations implement data governance effectively.

Question 25

How would you ensure compliance with new **data regulations**?

Answer 25

* Update policies * Assign responsible roles * Monitor data handling * Train employees and audit systems ## Footnote Proactive measures are essential for compliance.