{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/3385bfef758b477abdfb81f9d16d719e\" frameborder=\"0\" width=\"1600\" height=\"1200\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1200,"width":1600,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1200,"thumbnail_width":1600,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/3385bfef758b477abdfb81f9d16d719e-889d8ec160554b02.gif","duration":194.688,"title":"Global Electronic Sales Data Analytics Pipeline","description":"Hi guys, my name is Kennedy Agnaya, and this Loom is my Global Sales Data project using a CSV of global electronic sales data. I cleaned the dataset by removing empty rows and columns, then prepared it with pandas and numpy so it was ready for analysis. I did exploratory data analysis, feature engineering, and added more metrics and columns, then created visualizations with matplotlib and seaborn. I also prepared the data for Power BI and built interactive dashboards with insights like certain product categories performing better in specific regions during peak seasons. No action was requested from viewers."}