Analyzing customer purchase behavior, sales, and revenue. Final Dashboard after analysis in Power BI Introduction In this project, I’ll Identify the gender breakdown of Superstore company’s customer base , the most popular product categories for different age groups and genders , trends in sales and transactions over time , products that are in high demand, and product categories that are low in stock , and most profitable product categories . The analysis can be used to target marketing and sales efforts more effectively, improve product assortment and marketing campaigns, forecast future sales and make informed decisions about marketing and sales strategies, improve inventory management and prevent stockouts, and focus marketing and sales efforts on the most profitable areas. 1. About Dataset The source of the dataset is a subset of Sample superstore . It has 4 tables; Customer, Inventory, Product, and Sales. A ...
“Mindful Talks” is notebook in public. Here you’ll find straight-edge pieces on writing mechanics, practical data analytics, deliberate self-improvement, and the tech that stitches them together. I keep the prose lean, the numbers honest, and the takeaways actionable. If an article helps you tighten a paragraph, debug a dataset, or make a more considered decision, it earn.