🛍️ Retail Sales Dataset

This dataset contains transactional retail sales records across various departments and stores. It includes purchase data, departmental breakdowns, store location details, and individual salesperson information. This is ideal for performing analytics and BI use cases such as sales trend analysis, performance dashboards, and location-based insights.

📊 Dataset Description

Each row in the dataset represents a single sales transaction. The schema includes:

Column Name	Description
Department	Product category or department name (e.g., Cosmetics)
Manager	Department manager overseeing the sale
Salesperson	Staff member who completed the transaction
Transaction Type	Type of transaction (e.g., Purchase, Return)
Sale Amount	Total dollar value of the transaction
Sale Date	Date when the transaction occurred
Store Number	Unique identifier of the retail store
Country	Country where the transaction took place
StateName	State or region name
City	City and state code (e.g., Phoenix,AZ)
Zipcode	Postal code of the store

🧪 Sample Data

Department	Manager	Salesperson	Transaction Type	Sale Amount	Sale Date	Store Number	Country	StateName	City	Zipcode
Mens Furnishings	BRANCH	WEBB	Purchase	48.49	6/1/2011	281a	N/A	(not set)
Womens Shoes	ROBBINS	TAYLOR	Purchase	14.87	6/1/2011	577a	United States	Alabama	Birmingham,AL	35201
Casual	BURKE	ROGERS	Purchase	60.33	6/1/2011	211a	United States	Arizona	Phoenix,AZ	85019
Sportswear	COOLEY	GARCIA	Purchase	84.84	6/1/2011	576a	United States	Arizona	Mesa,AZ	85876

🧠 Possible Use Cases

• 📈 Sales Trend Analysis: Visualize department-wise or regional sales performance over time
• 🧾 BI Dashboards: Create dashboards in tools like Power BI, Databricks SQL, or Tableau
• 👥 Salesperson Performance: Evaluate individual or manager contribution to sales
• 📍 Geospatial Analysis: Map sales data by ZIP code or state
• 💳 Customer Segmentation: Classify purchasing patterns based on departments and amounts

📂 File Format

• Format: .csv, .parquet, or .delta (depending on usage)
• Encoding: UTF-8
• Delimiter: Comma (,)

📍 Getting Started

Use the dataset in Databricks, Pandas, or any data analysis platform:

📊 Key Business Questions for Your Sales Dashboard

🔹 Sales Performance Metrics

• What is the total sales revenue by department this month?
• Which departments have the highest YoY or MoM growth in sales?

🔹 Sales Team Performance

• Who are the top 5 salespersons by total sales amount?
• What is the average sale per salesperson by department or store?

🔹 Customer Behavior & Transaction Analysis

• What is the distribution of sales amount per transaction type?
• What is the frequency of purchases by department over time?

🔹 AI-Enhanced Insights to Ask Genie

• Which features most influence high sales (e.g., department, city, manager)?

🔹 Visual Elements to Include in the Dashboard

• Bar charts: Sales by Department, Sales by State
• Line charts: Daily/Monthly Sales Trends
• Maps: Sales by Zipcode or City
• Heatmaps: Sales per Department vs State
• Tables: Top 10 Salespersons / Managers / Stores
• KPIs: Total Sales, Avg Sale per Transaction, Number of Transactions

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