Data Analytics for Tourism and Hospitality Industry

1. Which of the following best describes the role of data analytics in the tourism and hospitality industry?

• Collecting raw data only.

• Providing clear pathways for well-informed decision-making through insights

• Generating reports without interpretation.

• Avoiding data usage in decision-making processes

1. Which era of data analytics introduced the concept of the enterprise data warehouse?

• Analytics 1.0

• Analytics 2.0

• Analytics 3.0

• Analytics 4.0

1. Descriptive analytics is primarily concerned with which question?

• Why did something happen?

• What is likely to happen?

• What happened?

• What should be done?

1. In the data value chain, what is the main activity in the 'Generation' stage?

• Data exchange

• Capturing information in a digital format

• Analyzing patterns in data

• Consolidating data from multiple sources

1. Who in an organization is responsible for cleaning, organizing, and predicting trends from data?

• Data Steward

• Data Scientist

• Data Engineer

• Functional Analyst

What is the predicted market value of big data analytics in the tourism industry by 2032?

• $100 billion

• $500 billion

• $200 billion

• $350 billion

Which technological advancement is NOT mentioned as contributing to the emergence of data analytics in the T&H industry?

• Cloud technologies

• Quantum computing

• New IT technologies

• Advanced infrastructure

Which of the following is NOT a benefit of using data analytics in the tourism and hospitality industry?

• Decreasing the volume of customer feedback

• Quickly reviewing large-scale volumes of data

• Gaining competitive advantage

• Better understanding customer preferences

Which of the following is NOT a reason for using data analytics-related techniques in the T&H industry?

• To predict hotel demand

• To improve staff recruitment processes

• To gain insights into customer preferences

• To analyze the impact of online reviews

Which component is NOT part of the challenges identified in data management for the T&H industry?

• Data Governance

• Data Integration

• Data Quality

• Data Visualization