Tag: power query editor power bi

Record Values – Structured Value In Power Query

Record Values – Structured Value In Power Query

This tutorial will discuss about record values inside the Power Query Editor. You’ll learn how to create and use records with different expressions to generate the results you want to achieve. Creating Record Values A record value is an ordered sequence of fields. It is made up of a set of fields that consists of

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Center Of Gravity Analysis In Power BI

Center Of Gravity Analysis In Power BI

Finding the center of gravity of a cluster of locations is a common task for people working with Geographic Information Systems. One example is when looking at the allocation of addresses to a depot or engineers to a working area. Although Power BI does not yet support true multiple dynamic layers in the map visuals,

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Huff Gravity Model Analysis in Power BI

Huff Gravity Model Analysis in Power BI

In this tutorial, we’ll learn how to do a Huff Gravity Model analysis in Power BI. We can use this analysis to estimate the potential sales or attractiveness of a certain store location. We usually do this in a Geographic Information System software. However, we can also do it in Power BI and make it

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Format Data In Power BI: Addressing Irregular Data Formats

Format Data In Power BI- Addressing Irregular Data Formats

In today’s blog post, we’ll discuss Problem of the Week #6. I’ll show you how to format data in Power BI involving the use of power query. The screenshot below is the solution that you should have after you’ve done all the data transformation. The actual balance number was $685,616.33. You can watch the full

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Power BI Query Editor: Row & Column Transformations

Power BI Query Editor Row and Column Transformations

In this tutorial, we’ll discuss essential transformations within Power BI Query Editor that can be used to optimize your rows and columns. In developing an intuitive Power BI model, it’s best to simplify your rows and columns inside your table. Optimizing your table is essential in creating visualizations, so you can easily recognize your data.

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