Chapter 14. Optimizing data models
In the previous chapter, you have seen some of the internals of VertiPaq. This knowledge is useful when you design a data model and you want to optimize it for quick execution of DAX queries. While the previous chapter was more a theoretical one, in this chapter we move on to the more practical side. In fact, this chapter describes the most important guidelines for saving memory and thereby improving performance when creating data models. As you learn here, your main objective will be that of reducing the cardinality of columns in order to decrease the dictionary size, improve the compression, and speed up any iteration and filter.
The final goal of the chapter is optimizing a model. However, before going there, ...
Get The Definitive Guide to DAX: Business intelligence with Microsoft Excel, SQL Server Analysis Services, and Power BI now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
