To analyze data in a relational database using SQL queries with the goal of supporting inventory-related business decisions that lead to the closure of a storage facility.
1) Where are items stored and if they were rearranged, could a warehouse be eliminated? 2) How are inventory numbers related to sales figures? Do the inventory counts seem appropriate for each item? 3) Are we storing items that are not moving? Are any items candidates for being dropped from the product line? 4) If we decrease the stocks by 5% for each of the products does it affect the sales? 5) Is price a major factor in popularity of the products? 6) What is profit percentage earned in the products that were sold the most? 7) What is profit percentage earned in the products that were sold the least?
We used SQL queries on MySQL Workbench to perform exploratory data analysis. To begin with, we with imported the database using the SQL script linked here- mintclassics DB and studied the schema using the EER (Extended Entity-Relationship diagram). Further, we identified the tables and fields that could provide relavent informations to the questions asked above and support our insights. We begin this project with analyzing historical sales data, identifying trends, and assessing stock levels. By reallocating orders, optimizing inventory, and considering price adjustments, the aim was to enhance operational efficiency, reduce costs, and maximize profitability while ensuring product availability and customer satisfaction. This approach aligns with modern supply chain principles and business management.
General Insights-
Problem-specific Insights
We also observed that a product named 1985 Toyota Supra (product code- S18_3233) had not been sold at all, On further investigating the product we observed that this product had not been priced yet. So the reason why it didn’t sell could be that it’s newly launched product or maybe there has been an error with the data entry.
Inventory primarily resides in warehouses A, B, and C, with warehouses A and B serving as primary shipping hubs, followed by warehouses C and D.