Daniil Zhemalskyi
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45 USD Retail Analytics Automation: ETL Pipeline (Python, MySQL,
Databases & SQLEnd-to-End project in the field of Data Engineering and Business Intelligence for retail sales analysis.
What was implemented within the project:
1. Automated the collection and cleansing of raw transactional data using Python scripts (Pandas and NumPy libraries were used). Duplicates were removed, and missing values and anomalies in data types were corrected.
… 2. Designed an optimal relational database model in MySQL, where cleaned datasets are automatically uploaded through a prepared pipeline.
3. Built a multi-page interactive dashboard in Power BI. A DAX language system was written for calculating complex business metrics and dynamic data filtering.
Key analytical insights of the project:
- Identified an overall seasonal sales plan exceedance of 5.26%.
- Segmented the target audience (in particular, the average check of the youth segment in the "Footwear" category was found to be 10% higher than the overall market indicator).
- Discovered patterns in the gender distribution of buyers, allowing for the optimization of marketing expenses.