Apache Spark 3 for Data Engineering and Analytics with Python - What was the Best Month in Sales?

The video tutorial guides viewers through setting up a SQL Analytics notebook to analyze sales data. It covers using a sales database, confirming table structures, and answering business questions like identifying the best sales month. The tutorial also demonstrates creating a bar chart visualization in Databricks, emphasizing SQL queries and data visualization techniques.

What is the first step in setting up a SQL Analytics notebook?

• Describe the sales table

• Select the workspace and create a new notebook

• Create a visualization

• Run a query to show tables

Why is it important to confirm the structure of tables before using them?

• To ensure the data is sorted

• To guarantee expected behavior

• To increase the speed of queries

• To reduce the size of the database

What SQL operation is used to calculate total sales for each month?

• ORDER BY

• LIMIT

• JOIN

• GROUP BY

Which month was identified as having the highest sales?

• December

• January

• November

• October

What is the purpose of using 'ORDER BY' in the SQL query?

• To calculate averages

• To filter the data

• To sort the results

• To join tables

Which type of chart was used to visualize the sales data?

• Bar chart

• Line chart

• Pie chart

• Scatter plot

What feature ensures consistent color themes across charts in Databricks?

• Chart designer

• Global color consistency

• Color palette selection

• Theme manager