Product Performance Dataset
Group Category: Dataset
Product Category: Database Design & Development
Sub Category: PostgreSQL
Monitor sales trends, evaluate product success, and optimize retail strategy with structured performance datasets
Business Overview:
The Product Performance Dataset offers a complete foundation for analyzing sales behavior, product efficiency, and inventory dynamics across a digital retail environment. By combining detailed product catalog data with transaction-level order histories, this dataset allows professionals to build data-driven insights on revenue growth, customer purchasing patterns, stock turnover, and product lifecycle performance. Designed for SQL users, analysts, and engineers, it mirrors real-world commerce environments with PostgreSQL-compatible formatting and clean relational structure.
Product Highlights:
- 5 CSV datasets:
products.csv,subcategories.csv,categories.csv,orders.csv, andorder_items.csv - Structured to support complex SQL queries involving sales, product hierarchies, and customer behavior
- Includes detailed data dictionary and table-wise breakdown of fields, types, and relationships
- Ideal for dashboarding, forecasting models, performance benchmarking, and SQL practice
- Perfect for data analysts, business intelligence teams, and data engineers
Learning Outcomes:
By using this dataset, you will:
- Analyze product-level and category-level sales performance using joins and aggregations
- Generate inventory turnover reports and pricing elasticity insights
- Develop sales dashboards with revenue, trend, and lifecycle metrics
- Forecast demand using historical order data
- Build SQL prototypes for retail ETL workflows and reporting systems
- Create intelligent recommendation models based on purchase behavior.
Dataset Document
| PDFThis documentation presents a detailed overview of a performance-focused dataset that links product catalogs with order transactions and sales analytics. It outlines schema definitions and analysis possibilities using product, category, order, and customer data.
Highlights:
- Describes 5 CSV tables with relationships across catalog, sales, and users
- Suitable for revenue optimization, demand forecasting, and inventory analysis
- Ideal for data analysts, BI developers, and product managers
products
| CSVHolds product-level data including names, descriptions, pricing, stock quantity, and subcategory links. It forms the foundation of the product catalog for sales and inventory analytics.
Key Features:
- 965 product entries
- Supports revenue tracking, pricing strategy, and inventory planning
- Linked to subcategories and order_items for integrated reporting
subcategories
| CSVContains mid-level product groupings with links to parent categories. Enables structured product classification and allows roll-up views of product performance.
Key Features:
- 68 unique subcategories
- Enables category-level slicing of sales and inventory reports
- Provides structural hierarchy for catalog filtering
categories
| CSVRepresents top-level product categories. Useful for high-level aggregation of metrics such as total revenue, order count, or top-performing segments.
Key Features:
- 10 distinct categories
- Forms root layer of the catalog hierarchy
- Supports performance benchmarking across product departments
orders
| CSVIncludes metadata about customer orders including status, total value, timestamps, and associated user IDs. This is the core transaction dataset enabling time-series and trend analysis.
Key Features:
- 11,473 orders
- Tracks order status, revenue, and customer linkages
- Supports sales pipeline monitoring and order conversion funnels
order_items
| CSVBreaks down each order into line items, linking individual products to orders with quantity and price data. Critical for item-level sales analysis and profit contribution metrics.
Key Features:
- Contains granular sales records for each product per order
- Supports unit-level performance tracking and discount analysis
- Enables product bundling and basket pattern detection
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About this Dataset:
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