Comprehensive Analysis of Retail Sales Data Part 1 - Dashboard

This project leverages a transactional dataset containing all transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based online retail business. The dataset was sourced from the    UCI Machine Learning Repository . I utilized advanced techniques like cohort analysis and RFM (Recency, Frequency, Monetary) segmentation to analyze customer behavior, identify trends, and support targeted marketing strategies.

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Key Methodologies and Tools:

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• Data Preprocessing: SQL and Pandas were used for cleaning, transforming, and adding new tables to enrich the dataset.

• Data Integration: Automated Python scripts were developed to scrape additional data from external sources, enhancing the dataset's comprehensiveness.

• Visualization and Analytics: Power BI was employed to create interactive dashboards, while DAX was leveraged for creating dynamic measures and calculations.