Microsoft Certified: Power BI Data Analyst AssociateVisualize and analyze the dataHard
A retail company wants to analyze customer behavior patterns using a Power BI report. They have transactional data including customer ID, product purchased, and transaction date. To identify which products are frequently purchased together, the data analyst needs to create a visual that shows associations between different products. Which type of visual or analytical technique is most appropriate for this task?
- AFunnel Chart
- BScatter Plot
- CMarket Basket Analysis (custom visual or R/Python)
- DHeatmap
Show answer & explanationAnswer & explanation
Correct answer: C. Market Basket Analysis (custom visual or R/Python)
Market Basket Analysis is a data mining technique used to discover relationships between items in large datasets. It identifies products that are frequently purchased together. While not a native Power BI visual, it's a common analytical technique that can be implemented using custom visuals from AppSource or through R/Python integration, making it the most appropriate choice for identifying product associations.
Why the other options are wrong
- A. A Funnel Chart visualizes stages in a process and is not relevant for identifying product purchase associations.
- B. A Scatter Plot is used to show the relationship between two numerical variables and is not suitable for identifying associations between discrete items like products.
- D. A Heatmap can show the intensity of a relationship between two variables, but it's not specifically designed for 'frequently purchased together' associations in the context of market basket analysis.
Market Basket Analysis
A data mining technique used in retail to identify strong associations or co-occurrences between groups of items (e.g., products frequently purchased together).
- Discovers 'what goes with what' patterns.
- Often uses metrics like support, confidence, lift.
- Can be implemented in Power BI via custom visuals or scripting.
Memory trick: Basket analysis finds links, what products are bought, what the customer thinks.