SAINADH

Analyzed logistics shipment data in Excel to evaluate delivery performance, cost, transit time, distance trends. Extended the analysis with RFM-based carrier segmentation to understand carrier utilization and spending patterns, supporting more data-driven operational decisions. My objective was to explore two practical business questions: How are delivery delays and shipment outcomes behaving across time and distance? How can carrier performance be evaluated using cost, transit time, shipment activity, and delivery performance? Starting with data quality I first reviewed the dataset for completeness and consistency. The initial cleaning process included identifying missing delivery dates and transportation costs, checking transit-day inconsistencies, and investigating numerical outliers. One thing I wanted to avoid was treating every unusual value as bad data. After null-value treatment, the working dataset contained 1,928 shipment records , while the dataset used after the selected ...

When I am introduced to a new project, one of my first priorities is  understanding the D ata Landscape, means how the Data is spread across. The sources are mostly from Excel and SQL databases for the structured data.  Before understanding the KPIs, dashboard behaviour, I'll try to understand below things What tables exist? (Must explain List of Tables and Overview of each) What does each table represent? ( Must explain in detail about each table) Which columns uniquely identify a record? (Keys present in the table or not to establish relations) Are relationships already defined? (To see if there's connectivity established or not) Note: There’s still a lot more to explore and analyze, but for this post, we’ll stop here. This is only the beginning — there’s much more analysis to come.  Here is the approach I follow for a database. 1. Start with Data Discovery — Understand What Exists My first step is going into the appropriate correct shcema/database and creating an inve...