Data-Driven Insights for Australia's Fashion Industry sales      

For this project, I conducted extensive ETL (extract, transform, load) processes on a large volume of sales data for two fashion stores in Australia. I utilized Python's powerful Panda library to efficiently extract the raw data, clean and transform it into a structured format, and load it into a suitable database for analysis.

Next, I delved into the data and applied a combination of quantitative and qualitative analysis techniques to gain valuable insights. These techniques included statistical analysis, data visualization, and customer segmentation analysis.

Finally, I created interactive dashboards using Excel and Power Query to effectively communicate my findings. These dashboards featured dynamic elements, allowing for easy exploration and reporting of the data. Overall, this project demonstrated my ability to proficiently manipulate and analyze data, and effectively present my insights through visually appealing and interactive mediums.