In a prior article, I illustrated and demonstrated the process of converting Tableau’s fixed level of detail (LOD) to Power BI. In this piece, I will extend this effort by guiding you through the translation of the EXCLUDE LOD to Power BI DAX.
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If you’ve navigated Tableau’s powerful Level of Detail (LOD) function, you know its complexity and potential for creating impactful visualizations. Now, whether you’re transitioning from Tableau to Power BI or need to excel in both platforms with limited Power BI skills, fear not! In this series, we’ll unravel the mysteries of applying Tableau’s three main LOD functions in Power BI.
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There are two types of measures in Microsoft Power BI models: implicit and explicit. Implicit measures are automatic and summarize column data in visuals.
Explicit measures, also referred to as just measures, are custom calculations you create for your model. Put simply, implicit measures are columns that can be aggregated automatically, while explicit measures are custom calculations defined using DAX, and is THE measure that we are familiar of.
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Need to connect Tableau to a dataset or semantic model in PowerBI(now Fabric)?It is not as difficult as you may think.
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In Power BI, you often has to decide whether to create a column or measure to achieve your analytic goals, though they can be used inter-changeablely in a many cases, they are very different in how they function and perform.
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It happens sometimes that the report metrics usage report suddenly stopped refreshing, you waited 24 hours as suggested and click on that refresh button hundreds of times and still no new data, then you tried to check the semantic model, it gives this sad message.
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If/esleif/else is one of the the most used functions in Tableau calculation and unfortunately, it can not be applied verbatim in Power BI to achieve the same goal. The equivalent function in Power BI DAX language is the Switch() function and it works especially well on multiple scenarios, it can be used to convert either if/elseif/else statement of possibly case/when query in Tableau.
Continue readingUsing the superstore dataset, supposing we have a certain order quantity target we want to evaluate on all states and give dynamic feedback based on how well we met that target. But this time, we want to do it in Power BI.
Start with same base structure:
Parameters are useful when you want to add interactivity and flexibility to a report, or to experiment with what-if scenarios. Using the superstore dataset, supposing we have a certain order quantity target we want to evaluate on all states and give dynamic feedback based on how well we met that target.
Converting a highly intricate Tableau report to Power BI, or vice versa, might seem daunting at first. However, I’ve discovered that it doesn’t have to be overwhelming if you approach it methodically, breaking it down into manageable steps. It becomes even simpler if we begin with a foundational report or data source, such as the widely-used Superstore data source. For this particular scenario, I opted for the Tableau data source instead of the Power BI AdventureWorks, as the Superstore data source is more accessible and user-friendly.
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