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Utilized SQL to build a query that would pull every shipment Home Depot tendered, as well as its status and location - connected query to Excel, allowing data to autopopulate. Added Python script to refresh data four times daily, and wrote an Excel formula to calculate driving distance from location to destination, presenting time and distance. Spreadsheet would automatically flag if there were any errors, delays, or concerns with the shipment. Click the photo to view the training presentation.
Wrote a SQL query to replace a previous query advising whether connected shipments had become unconnected. This saved us hundreds of thousands of dollars per month, as if we missed a batch it would cost over $30k per day. Previously specialists would have to manually check every batch they ran to see if it broke.
To get familiar with PostgreSQL and database building, I took public data from the MET and imported it into Excel. I cleaned the data, then wrote a formula to put the information in the correct syntax so that I could copy and paste it into the database using SQL.
Please find all of my Python projects on Repl.it