microsoft adventureworks database download 2014

Reseller Sales generated 5 times more sales than Internet Sales and 7 times more profit, with Vigorous Exercise Company being the reseller that had the highest amount of orders. In the example below, I selected the dates – and the country Canada.

The period can be filtered by choosing the Start Date and the End Date, by simply dragging the circles to the right or to the left, respectively or by clicking on the date and choosing one from the calendar. All the data can be filtered out by category, subcategory, or client occupation as well. Top 10 Resellers is also visible in one of the tables. It is also clearly visible that Reseller Sales generated the highest profit, 66.82% compared to Internet Sales that generated only 41.15% profit. The data can be filtered per each country, in order to see the products that generated the highest sales and how many from these products were sold via Internet or via Resellers. In the Sales Analysis by Region it is visible on the map that the highest amount of orders happened in the United States, followed by the United Kingdom in Europe. As far as the return rate is concerned, bike tires appear to be returned the most often. Components were ordered the least often, followed by clothing. When filtering the dashboard by year 2013, bikes appear to generate the highest revenue, while accessories like water bottle or patches were ordered most often. If no year is selected, then the dashboard will show all the data accumulated for the years 2010, 2011,2012,20, as the rest of the years have been filtered out from all the pages. Once it is selected, all the data will be filtered by that selected year(s). To start with, the Sales Dashboard contains a top slicer, where the year can be selected. I used both M language and DAX to normalize my data and to create the visuals that seemed relevant.

This database is generally used by trainers for demos and labs, and it is indeed a great place to start practicing your newly acquired skills and knowledge. For this analysis I used the Sample Database Adventureworks 2014, that I imported into Power BI from Microsoft SQL Server.

Microsoft adventureworks database download 2014