In this chapter, we learned about the data modeling techniques. We started with learning about the basics of data modeling. We looked at two types of data modeling: entity relationship modeling and dimensional modeling. We looked at dimensional modeling in detail and learned about the two widely-used data modeling schema: the star schema and the snowflake schema. We learned about which schema works best with Qlik Sense and why.

Moving ahead in chapter, we learned about different types of joins. We learned about what type of join is used for what purpose and what kind of output they generate. Then we looked at the pitfalls of using joins. It is important to keep thses in mind while using joins. Then, we learned about concatenation and the scenarios in which we should use the concatenation option. We also looked at automatic concatenation, forced concatenation, and NoConcatenation.

Further, we learned about the ways in which data can be filtered while loading in Qlik Sense. We also learned about QVD. We understood why we should use data loading from QVD, and not from direct data source.

Then we learned about the link table, which is used when you want to link multiple fact tables with different granularities of data. We learned about the way in which multiple dates can be handled in Qlik Sense using the concept of canonical dates. We saw that the best option is to create the accumulations and rolling averages in the script using the As-Of Table. Lastly, we learned about the various options to keep our Qlik Sense scripts as optimized as possible to get better performance.