We will now start looking at the components that make up the Sales Analysis dashboard so that we can leverage them to make improvements.
Although the text title on the left-hand side of the straight table (Segment Change in Revenue vs Last Year) does not change, you can change what is displayed in the straight table, Segment Changes in Revenue, using the Group button in the upper left corner of the table (see Figure 5-3):
This button looks like a circular arrow; if you hover over it, the word Cycle pops up in a box. The button allows you to scroll through group measures selected for the table. Provided at least two or more expressions are available to create a group, the Group button can be used in transforming merged group expressions of dimensions or measures into one or more cyclic groups.
In the QlikView layout, you can cycle through the expressions belonging to one group by clicking on the cycle icon that is displayed in the chart (cycle group). Right-click on the same cycle icon to get a pop-up list of the expressions belonging to the group that are currently unused for direct selection.
To investigate, change or add a group to the Changes in Revenue straight table.
Total Group
.Notice how your new cyclic group is now in the straight table inside the other cyclic group. Experiment with how selections in one group affect the other and how selections in multi-boxes in containers affect both groups.
At this point, you can choose to save Executive Dashboard
as a new QlikView document with a different name. I chose Executive Dashboard – Diane
. You still will not be able to reload the script because you do not have access to the QlikView server, but you can save your changes to the sheet objects this way.
Now, we will examine the larger components of the Sales Analysis dashboard. Start by clicking on the sheet in a vacant area and choosing Properties. Then, navigate to the Objects tab. Here, we can see all objects that make up the sheet and their IDs, Types, and other properties.
Click on a specific row in the tab, and it will activate the two buttons, Delete and Properties, in the lower-right corner of the wizard. If you click on the Delete button, it will actually delete the object from the sheet. If you click on the Properties button, it will pop up another wizard with the ability to edit the properties for the object you selected.
Here, we can see that we have two straight tables, one line chart, one combo chart, one container object, and multiple other formatting and informational objects.
You will now see the Properties box for the container object; it shows that container object contains eight multi box objects.
Multi boxes in a container allow us to further filter our data. As noted before, the spacing is not quite right inside the container, and we cannot see the multi box or its label for Country. You can still click on it and choose a country as a filter, but it is difficult to see.
Now, we will add the container to the right-hand side of the Sales Analysis sheet.
Size the container with the mouse and white-filled, double-ended arrows by hovering near a container edge, and then by left-clicking when you get the arrow. It is actually easiest to move your container by changing the size. Now, you see what looks like one object on the sheet, a tiny letter A in a gray box, and another gray box that says Age Profile and shows a pie chart and key, as shown in the following screenshot:
If we click on A in our new container, the chart image is replaced by a giant picture of the word QlikView, which is so big that only part of the image can be seen. If we now click on the Age Profile button in our new container, the display returns to the pie chart. If we click on the Age Profile key or an area in the pie chart in our new container, the pie chart goes to the first key color displaying a single circle, and the one key item selected now changes to 100%. Too bad there isn't an easy way to change the pie chart to retain the key and key color change when selected. Perhaps, we could use something like alternating visibility charts, such as the ones used on the KPIs tab. We leave that exercise to you. Interestingly, nothing on the AR Analysis tab seems linked to this chart but, by adding the Age Profile chart to the Sales Analysis tab, we can filter data in both straight tables readily visible in the top half of the screen. Also, clicking on the pie chart a second time returns it to the original multi-slice display.
If we navigate to the Customer Profitability straight table and click on the customer, J.S. Lee Associates, our display changes, and J.S. Lee Associates now shows up in the multi box for Customer. Also, the pie chart in Aging Profile switches to show two keys that tell us that this customer has accounts receivable falling into two categories, current and between 1 and 30 days past due. That is very interesting information, but we might be better served if we created a new tab for Customer Profitability, where we could investigate this kind of information without interfering with Sales Analysis.