Power BI Masterclass - DAX - Cohort Customer Order Analysis

The video tutorial covers cohort analysis by visualizing order dispersion and creating measures in Power BI. It explains how to create measures and columns, understand context transition, and use the calculate function. The tutorial also demonstrates creating a measure for distinct customers and building stacked column charts to analyze customer orders over time.

What is the primary purpose of using the order ID in the sales table?

• To count distinct orders

• To track product inventory

• To identify unique customers

• To determine the total sales amount

Why is context transition important when using measures in Power BI?

• It automatically updates data sources

• It allows for faster data processing

• It ensures measures are calculated in the correct filter context

• It simplifies the user interface

How can you ensure that a measure is calculated in the correct filter context?

• By creating a new table

• By using the FILTER function

• By wrapping the measure in the CALCULATE function

• By using the SUM function

What is the reason for creating a measure to count distinct customers?

• To calculate total sales

• To filter data by product category

• To visualize customer data as a number

• To directly modify the customer table

In the context of the video, what does the stacked column chart represent?

• Inventory levels across different regions

• Employee performance metrics

• Distinct customers and their order amounts over time

• Total sales by product category

What does the distinct count of customer orders help analyze?

• Product popularity

• Customer cohorts based on order frequency

• Customer loyalty

• Sales trends over time

What is the significance of the first order date in the cohort analysis?

• It predicts future sales trends

• It helps categorize customers into cohorts

• It determines the customer's lifetime value

• It identifies the most popular products