Sales
Delivered orders generated approximately $13.22M in GMV. São Paulo contributed around $5.07M, or approximately 38% of the total.
About the Project
I started with six raw CSV files, checked and transformed the data using DuckDB and SQL, and created separate order-level and item-level datasets. I then used those datasets to build three interactive dashboards in Tableau Public.
Business Questions
- How did delivered GMV change over time?
- Which states contributed the most delivered GMV?
- How many delivered orders arrived on time?
- Did late deliveries receive lower customer reviews?
- Which product categories generated the most value?
- Which categories experienced greater freight pressure?
Interactive Dashboard
Use the dashboard tabs and filters to explore the Executive Overview, Delivery and Customer Experience, and Product Performance pages.
If the dashboard does not load, open it directly in Tableau Public .
Key Findings
Delivery and Experience
Approximately 91.9% of delivered orders arrived on time. On-time orders received an average review score of 4.3, compared with 2.6 for late orders.
Freight Pressure
Among the leading categories by GMV, furniture décor had a freight-to-GMV ratio of approximately 23.7%, followed by housewares at 23.2%.
How I Built It
- Loaded six public Olist CSV files into DuckDB.
- Checked row counts, keys, missing values, statuses, and dates.
- Built order-level and item-level analysis tables using SQL.
- Exported the processed data for Tableau.
- Created and published three interactive dashboards.
- Documented the process, findings, and limitations on GitHub.
Limitations
The dataset is historical and includes partial years. GMV represents product value rather than company revenue or profit. Relationships found in the data also do not automatically prove cause and effect.