IT agility can be increased by improving the quality of the data, for instance, by creating enterprise data standards. However, how can you increase data quality if you can't see the problems in the data? Data quality isn't just about wrong numbers or missing data. It can also refer to surplus data stores that your IT team end up looking after unnecessarily.
This is where Tableau steps in. By making data accessible and visible, the issues are made visible for all to see. It's at this point that the business needs to decide whether to tackle the problems head on or go along as they did before.
Sometimes people don't like numbers. Numbers can deliver hard news, for example, something like job losses might be on the cards. People need to be completely sure of the data so they have confidence that they are taking the right decisions. People need to prove to themselves and their managers that the numbers are correct.
The information-seeking mantra defines drilling to detail as a key concept of people interacting with their information. This is particularly important if the numbers show a message that the business consumers do not like.
When looking at the details, it is important to work out what details we want to see. Sometimes, people will want to see the detailed data behind the whole workbook. On other occasions, they will simply want to see the data that lies behind the particular dashboard that is currently on view. In this recipe, we will look at both of these scenarios.
In Tableau, it isn't possible to export all of the data at the dashboard level. Instead, you need to export data at the worksheet level only. Therefore, if you go to a dashboard and try to export data, you would see that the option is grayed out. This makes sense because the dashboard-level data may appear confusing if it is placed in a crosstab format, and it may be hard to relate the columns to their appearance on the dashboard.
You can select the option Export the data to CSV. However, this will only export the data for the specific data points that you see. If you want to export all of the underlying data, then you need to select the Underlying tab rather than the Summary tab. It is easy to miss this step, and we will call it out in this recipe.
- To export all of the data, go to the
KPI Shapesworksheet. - Go to the Worksheet menu item and then choose the option Duplicate as Crosstab. You will then generate a new worksheet that has a neat crosstab which displays all of the data.
- Rename your new worksheet as
KPI Shapes Crosstab. - Now, we will export just a part of the data rather than the whole set. If you want to simply export the data of one particular data point, right-click on the data point.
- Click on the Above label for Australia and you will see a pop up appear.
- Click on the View Data… button at the bottom right-hand side of the pop-up window that will appear. You can see an example of this in the following screenshot:
- Now, you will get the following View Data dialog box which opens on the Summary tab, as shown in the following screenshot:
- Click on the Underlying tab to reveal all of the data. You can see this at the bottom-left of the View Data dialog box.
In this recipe, we took a dashboard and conducted various exports on the data. We exported all of the data and then looked at taking filtered exports based on the data displayed on the screen. We also looked at obtaining the underlying data which supports the summary that we see on the screen.
When you create a new crosstab worksheet, you could use this crosstab as the basis for further visualization or to export data to other packages such as Excel.
It is also good for checking the data. People get comfort from knowing about the data from the cradle to the grave, particularly if the data is contentious.