Topic: VertiPaq
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The second edition of the Optimizing DAX video course is available: new content, a new book, and some on the behind-the-scenes of the project. Read more
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This article describes how to implement a DAX measure to run faster than what you get from the built-in fusion optimization. Read more
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Horizontal fusion is a new optimization technique available in DAX to reduce the number of storage engine queries. In this article, we introduce this optimization with some examples. Read more
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Analyzing table and column size is an important step in optimizing a data model for Power Pivot, Power BI, or Analysis Services Tabular. This article describes VertiPaq Analyzer, an Excel workbook to analyze detailed information extracted from Dynamic Management Views. Read more
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This article explains the roles of the formula engine and of the storage engine used to execute DAX queries. Read more
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This article contains a short checklist of what you have to do in order to optimize the memory used by a data model in PowerPivot or in Analysis Services Tabular, including links to tools and resources that can help you… Read more
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Hardware and virtualization settings have a big impact on Analysis Services Tabular performance. This article describes best practices for the most important settings to check. Read more
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Choosing the right hardware is critical for a solution based on Analysis Services Tabular. Spending more does not always mean having a better machine. This short article describes how to choose the right server and, as you will see, the… Read more
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The DIVIDE function in DAX is usually faster to avoid division-by-zero errors than the simple division operator. However, there are exceptions to this rule, described in this article through a simple performance analysis. Read more
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A common best practice is to use CALCULATETABLE instead of FILTER for performance reasons. This article explores the reasons why and explains when FILTER might be better than CALCULATETABLE. Read more