Sales Dashboard
This Dashboard was created using Power BI, measures were formed using DAX Code. Using a SuperStore Data Set from the years 2015-2017.
Steps taken in analysis:
- The relevant data was extracted, transformed and loaded into Power BI using Power Query.
- Measures were formed using DAX code.
- Visual KPIs within the titles were created using conditional formatting.
- Additionally, bookmarks were utilised to facilitate the analysis of sales, quantity, and profit of each visual.
Overview:
- This Dashboard was created to analyse the data set over three main measures: sales (total revenue), quantity (total sold), and profit (total revenue - total costs). This was done for each year during the period of 2015-2017, and each year can be analysed individually using the slicer at the top left.
- KPIs are displayed at the top of the dashboard to clearly visualise the total values for each measure. With the percentage (%) change of each total from the previous year (PY) additionally highlighted above. A green circle indicates a "positive" change and a red circle indicates a "negative" change.
- A somewhat static visusalisation which is not affected by the change in measure (sales, quantity, profit) only year, in the middle of the dashboard is utilised to provide insight regarding into total orders and total returns for each product type. This visual also follows the same %PY and colour format as our KPIs above. Yet, an increase in total returns from previous year (PY) is indicated with a red circle as this is a "negative" change (as an increase in total returns is not a positive outcome).
- Customer demographics and also visualised in this dashboard, allowing us to form associations and explore variations across our three measures (sales, quantity, and profit) by customer segment, region, and state.
- This dashboard details the top 5 products within each product category, which can also be further analysed across our three measures.