Week-2 DGES

Which role is primarily responsible for ensuring that the data governance strategy aligns with business goals?

• Data Steward
• Data Architect
• Data Governance Officer
• Data Analyst

What is the primary goal of data governance in an organization?

• To store large amounts of data efficiently

• To ensure data is managed and used in compliance with policies and regulations

• To collect as much data as possible

• To automate data entry processes

What is the main difference between data governance and data management?

• Data governance involves overseeing policies, while data management executes the technical handling of data

• Data governance is reactive, while data management is proactive

• Data management sets standards, while data governance stores data

• Data governance only applies to government agencies, while data management applies to all organizations

Who typically assumes responsibility for the day-to-day management of data quality?

• Data Scientist
• Data Steward
• IT Manager
• Data Custodian

Which role focuses on designing the technical infrastructure and tools for data storage and access?

• Data Engineer
• Data Analyst
• Data Architect
• Data Governance Officer

Who ensures that the organization complies with relevant data protection regulations?

• IT Manager
• Data Custodian
• Data Governance Officer
• Data Engineer

What is a common consequence of poor data governance in an organization?

• Increased business opportunities

• Data breaches and non-compliance with regulations

• Improved customer trust

• Better data analytics

Which of the following best describes ‘data quality’?

• The number of data points stored in a system

• The overall accuracy, completeness, and reliability of data

• The format used to store the data

• The speed at which data can be processed

Which role typically assumes responsibility for interpreting data and generating insights?

• Data Scientist
• Data Steward
• Data Engineer
• Data Analyst

Which of the following is a benefit of implementing a successful data governance framework?

• Higher operational costs

• Increased organizational friction

• Improved data-driven decision making

• Difficulty in regulatory compliance