An analysis of the historical data of a company which sells products and ships them to its customers' destinations was conducted in order to determine the future cost effective shipping methods and approaches.
A historical dataset with 1000,000 rows and 13 columns spanning 8 years. Data is stored in a single table.
- Analysis of orders shipped within seven days, within one month, and after 30 days of placing the order.
- Linked transaction, order, COGS, revenue, and net profit options buttons to the charts. If an option is selected on a chart, the selected option is displayed on all charts except those with shipping intervals.
- Easy-to-read cards visualize important KPIs for rapid decision-making.
Country, years, and quarters
- Utilized Power Query to extract and transform the data, then transferred the data to Power Pivot for further analysis.
- Power Pivot is used to store the data for further exploration in the future, if the number of rows increases into the millions.
- Implemented OFFSET and COUNTA functions to prepare reports that interpret transaction, order, COGS, revenue, and net profit on a monthly and quarterly basis, by sales channel, by sales regions and by item types sold over time.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent