Our last overview on BI instruments was dedicated to Redash, but today we will deal with the dashboard in QlikSense using the SuperStore Sales dataset. The dashboard was built for us by Alexey Grinenko, a head of BI section, Business Solutions Development Department at Softline.
To load data in QlikSense we need to use load scripts. This is how the script looks:
Basically, the script lists the columns that we need to import and the link to a file. [Calendar_Order] script makes a custom calendar as all our data is before 2012 and the default calendar creates measures such as *current month* or *previous month* which we don’t need.
As you can see, the dashboard has the same structure as in Tableau with some peculiarities of QlikSense.
At the top, there is a line with KPI cards. The cards compare KPI values in the chosen year with the values in the previous one and show the change in percentage. If the change is positive, the percentage is displayed in green, if the change is negative, values are red.
Then you can see a treemap which shows provinces by profit. The color shows profit distribution in the provinces. As all charts in QlikSense, the treemap is clickable and we can choose several provinces and see only the data related to them. On the right of the treemap, you can see area graphs that show profits by month in 4 different years.
At the top right corner of the dashboard, we have a drop down menu where we can choose a month and a year. As QlikSense doesn’t have this feature as default, we had to customly create such a calendar in a load script. First, we loaded the Month and the Year columns and created a third column where we concatenated Month and Year with a dash. This measure will later help us in switching the periods.
In the next part of the dashboard, we can see the analysis of products and customers. On the right, there is a bar chart that shows profit and sales by categories. On the left, the bar chart displays the Top 15 products by profit. In the settings, we can change this number and display fewer products if we wish.
Last but not least, we have a bubble chart which shows the distribution of customers by profit and sales. Each bubble represents a customer and the size of the bubble shows the number of orders. The color indicates the size of the discount.
Together with Alexey (his scores are in brackets) we have evaluated the dashboard on 10 points scale (10 being the highest score) and received the following results:
- Meets the tasks – 10
- Learning curve – 6.9 (8)
- Tool functionality – 9.0 (7)
- Ease of use – 7.3 (8)
- Compliance with the layout – 9.8 (9)
- Visual evaluation – 7.5 (10)
Overall: 8.4 out of 10.