When you have loaded your data into Qlik Sense, you need to look at how the data is structured and arrange it to mirror the kind of data model you want to achieve.
Your goal should be to create a data model that enables efficient handling of the data in Qlik Sense. Usually this means that you should aim for a reasonably normalized star schema or snowflake schema without any circular references, that is, a model where each entity is kept in a separate table. In other words a typical data model would look like this:
- a central fact table containing keys to the dimensions and the numbers used to calculate measures (such as number of units, sales amounts, and budget amounts).
- surrounding tables containing the dimensions with all their attributes (such as products, customers, categories, calendar, and suppliers) .
Information noteIn many cases it is possible to solve a task, for example aggregations, either by building a richer data model in the load script, or by performing the aggregations in the chart expressions. As a general rule, you will experience better performance if you keep data transformations in the load script.
Tip noteIt's good practice to sketch out your data model on paper. This will help you by providing structure to what data to extract, and which transformations to perform.