In this tutorial, you’ll learn about how the storage engine can use the data model to compute information for your DAX calculation. It has the ability to use Left Outer Joins via the data model. The storage engine can do simple joins by having a one-to-many relationship in your data model or by using the
Tag: Power BI Optimization
This post will discuss how to identify a filter via xmSQL and the storage engine query in Power BI. You’ll also learn what VertiPaq is doing when you filter on range. This is an important topic because the cardinality of what’s being applied in the filters is the biggest driving force of DAX’s performance. xmSQL
Today’s post will talk about how the storage engine in Power BI can do mathematical operations. This tutorial is helpful if you want to get combined figures without a column or a table. When dealing with easy measures or codes, the best practice is to send them into the VertiPaq storage engine. Unlike the formula
In this tutorial, you’ll learn about xmSQL aggregations. You’ll also understand how a storage engine in DAX Studio can greatly improve your report’s performance. There will be sample aggregations shown and used so that you can see how they perform in VertiPaq. There are two types of engines: the formula engine and the storage engine.
This tutorial will discuss about RowNumber in DAX Studio. This can be a source of confusion because it shows up at some storage engine queries but it doesn’t exist in your data model. You’ll learn how these obstacles are generated, how they affect the whole calculation, and how to deal with them. RowNumber shows up