Apache Spark 3 for Data Engineering and Analytics with Python - Challenge Part 3 - Q4 Products Bought Together

The video tutorial addresses a complex question about identifying products frequently sold together in New York. It guides through setting up a data analysis environment using PySpark, preparing and filtering data, and aggregating it to create product lists per order. The analysis reveals that the Google phone and USB C charging cable are often bought together. The session concludes with a summary of findings.

What is the main question being addressed in the analysis?

What method is suggested to collect a list of products sold together?

What criteria are used to filter the orders in the analysis?

What steps are taken to ensure the data is accurate before analysis?

What is the significance of the 'product list size' in the analysis?

How are the products that are frequently bought together identified?

What conclusion can be drawn about the Google phone and the USB C charging cable?