__STYLES__
The dataset is gotten from kaggle. The dataset contains 10 columns and 1,232,867 rows. I created new column for age categories to bring out meaningful insight from the dataset.
DAX was used to calculate columns and measures. I calculated Current Year (CY), Previous Year (PY) , Year-on-Year (YoY), total revenue, total customers and total quantity.
Relationship was created in power pivot between the calendar table and the dataset.
Business Case:
Do we have best preforming mall?
Do we have any worst performing category?
What age category and gender are our top customers?
What is the demographic distribution of customers?
Key Insight:
2 the analysis shows that clothing category is the worst performing category from 2021 - 2023.
Youth were top customers from 2021 - 2022. While elderly were top customers in 2023. Although adults and teens shop at the mall, they have never emerge as top customers a cross all malls. 57.7% of the top customers are female compared to 43.3% who are male.
59.8% of customers are female. 40.2% are male. 38.8% are youth. 38.2% are elderly. 19.3% are adults and 3.8% are teens.