what is fresh-produce-retail-analytics-sql-and-power-bi-capstone-project fr?

This is a data analytics portfolio project that analyzes over 800,000 sales transactions from a fresh produce retailer, covering July 2020 through December 2023, to find what drives profit, where operations lose money, and how customers behave. The project sets out to answer 10 specific business questions grouped into three areas: financial analysis, operations and spoilage, and customer behavior. The work has three main parts. First, a PostgreSQL file called sql_views.sql that contains 10 SQL views built with multi-table joins, common table expressions, aggregations, and window functions to answer each business question. Second, a three page Power BI dashboard covering financial analysis such as revenue and profit, operations and spoilage such as waste costs and seasonal patterns, and customer behavior such as peak selling hours and returns, with date filtering and page navigation built in. Third, a written findings report summarizing the business insights and recommended actions. Among the specific questions the project tackles are which product categories generate the highest revenue versus the highest profit margin, how discounting affects quantity sold and total profit, which products cost the most in wasted stock, whether spoilage follows seasonal patterns, and which hours of the day see the busiest sales and highest return rates. The README shares some of its key findings directly: total revenue of 3.37 million dollars with a net profit of 1.03 million dollars, an annual waste cost of about 210,000 dollars from over 46,000 spoiled units, a median loss rate of 9.43 percent, and a peak sales hour of 4pm. It also reports that discounted items generate 75 percent less profit than items sold at full price. To use the project, a reader needs PostgreSQL and a tool like DBeaver to run the SQL views, plus Power BI Desktop to open the dashboard file and connect it to a database or CSV exports. The author describes it as part of a personal data analytics portfolio and asks that it be credited if referenced, though it uses no formal open source license.