In this chapter, we learned about some of the techniques we can use to help us optimize our data models. We learned that reducing a data model's memory requirement is a major consideration in the overall design process.
We started off by learning about the VertiPaq compression engine. We looked at what it is and how it works, and why this knowledge is essential if we want to effectively optimize our data models. Next, we learned about data profiling, and how this can help us identify what data to include in a data model. This included a look at the data profiling capabilities of Power BI Desktop, along with some other tools that are available to help with this process.
We then learned about some of the ways we can simplify the structure of our data models looking at column cardinality, column storage, and identifying the correct columns to store. Finally, we looked...
