Definitive Guide to DAX, The: Business intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel, 2nd Edition
by Alberto Ferrari, Marco Russo
Chapter 18Optimizing VertiPaq
The previous chapter introduced some of the internals of VertiPaq. That knowledge is useful to design and optimize a data model for a faster execution of DAX queries. While the previous chapter was more theoretical, in this chapter we move on to the more practical side. Indeed, this chapter describes the most important guidelines for saving memory and thereby improving the performance of a data model. The main objective in creating an efficient data model is to reduce 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, the first and most important skill ...
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