Apache Spark 3 for Data Engineering and Analytics with Python - Get the Right Time to Advertise

The video tutorial explores the optimal timing for displaying advertisements to maximize customer purchases. It involves extracting purchase hours from order data using SQL, caching queries, and counting orders per hour. The analysis identifies peak purchasing hours, and the data is visualized using line charts. Adjustments to the charts are made to ensure clarity and accuracy in representing the data.

What is the primary goal of determining the purchase hour for each unique order ID?

• To find the most popular products

• To maximize advertisement effectiveness

• To reduce operational costs

• To improve customer service

Which SQL function is used to extract the hour from the order date?

• HOUR

• EXTRACT

• TIME

• DATEPART

What is the purpose of caching the query as a temporary table?

• To calculate the number of orders per hour

• To simplify data visualization

• To store data permanently

• To improve query performance

How are the busiest hours determined in the analysis?

• By analyzing customer feedback

• By grouping and ordering the data by hour

• By counting the number of unique products sold

• By calculating the average order value

What is the final step in visualizing the data?

• Exporting the data to a spreadsheet

• Creating a bar chart

• Ordering data by hour in descending order

• Adjusting chart settings for clarity