The Costs of Poor-Quality Data

The video discusses the importance of data quality, highlighting a case where a GPS error led to a house being demolished. It explains the concept of 'fit for purpose' data and the consequences of poor data quality, such as financial losses and compliance issues. The video also covers data compliance standards like GDPR and HIPAA, and the challenges organizations face due to poor-quality data. It emphasizes the need for systematic data quality management and outlines the characteristics of high-quality data, including accuracy, relevancy, representation, and accessibility.

What was the cause of the house being demolished in the example?

• A legal dispute

• A natural disaster

• A GPS error on Google Maps

• A construction mistake

What does 'fit for purpose' data mean?

• Data that is stored securely

• Data that is easy to access

• Data that fits the intended use

• Data that is visually appealing

What is a potential consequence of poor data quality in marketing?

• Higher return on investment

• Improved brand reputation

• Increased customer satisfaction

• Wasted media budget

Why is managing data quality considered expensive and time-consuming?

• Because it involves complex technology

• Because it should focus on critical data

• Because it requires hiring more employees

• Because it needs constant updates

What is metadata's role in data quality management?

• It provides a backup of data

• It helps in understanding data flows

• It encrypts sensitive data

• It visualizes data trends

Which of the following is NOT a characteristic of high-quality data?

• Accessibility

• Relevancy

• Complexity

• Accuracy

How can poor-quality data affect a company's performance?

• By leading to inaccurate analysis

• By improving customer service

• By increasing market share

• By enhancing product quality