In Chapter 3, Building Data Models, we looked at the importance of building a well-structured data model. In this chapter, we'll take the practice of data modeling one step further by learning about some of the techniques behind data model optimization. As a tabular data model resides in random-access memory (RAM), reducing its memory requirement is a major consideration in the overall design process.
We will start this chapter with an introduction to the VertiPaq compression engine. We'll look at what it is and how it works, and how this knowledge can help when it comes to optimizing the data in our data models. We'll investigate data profiling and how this can help identify what sort of data we should include in our data models, and we'll look at some of the tools available that can help with this process.
Then, we'll learn...