In this chapter, we saw how to use Qlik Sense to create an application that helps us to analyze our customer data. We used a simple dataset with just 440 customers that we downloaded from the University of California website mentioned earlier. The dataset contained only two dimensions—channel and region—and six measures—Fresh, Frozen, Milk, Grocery, Delicatessen, and Detergents_Paper.

We learned how to load a dataset from a CSV file. We created a data model and uploaded additional tables created in a spreadsheet editor. Finally, we saw that we can create additional fields in a table using the spreadsheet editor or the data load editor. We also saw that the data load editor provides a lot of control over the data.

After creating the data model, we learned what associative logic is and how a business user can slice and dice his data using it.

Finally, we learned how to create basic visualizations using Qlik Sense, and we created our first Qlik Sense app.

In the next chapter, we'll use Rattle to segment the customers automatically based on their annual money spent in the different product categories. This segmentation will show us the data in a different light.

In Chapter 8, Visualizations, Data Applications, Dashboards, and Data Storytelling, we'll improve our knowledge of Qlik Sense and learn to create useful and attractive visualizations.