I developed a Sales Analytics Dashboard for a pharmaceutical company to make sales performance easier to monitor and understand. The main challenge was bringing different sales views into one report while keeping the information relevant to the current reporting period. The dashboard provides current-month performance alongside historical trends, helping compare actual sales with budget and previous periods. It also includes predictive sales information to support forward-looking analysis.
I built the dashboard using tools such as Power BI, SQL, Excel, Python, DAX, and Power Query. I focused on creating dynamic date logic so that the report automatically reflects the current month and updates the relevant sales views. I also created measures and calculations for sales comparisons, cumulative performance, and forecasting. Interactive filters allow the analysis to be explored by business type, division, zone, region, product type, and brand.
Through this project, I improved my skills in data preparation, data modelling, DAX calculations, and dashboard design. I also learned how to combine historical sales data with predictive analysis and dynamic time-based reporting. The project helped me understand how a well-structured dashboard can turn raw sales data into clear information for analysis and decision-making.
