Tag: Power Query

Power Query M Language Tutorial on Projections

Power Query M Language Tutorial on Projections - Enterprise DNA

The field-access expression is used to select a value from a record or to “project” a record or table to one with fewer fields or columns, respectfully. In this Power Query M Language tutorial, we are going to delve on Projections, its meaning, and how to use it. You can watch the full video of

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Replace Value For Matching Text In Power Query

Replace Value For Matching Text In Power Query - Enterprise DNA

If you’ve ever had a requirement to perform multiple exact text match replacements, there’s a good chance you’ve performed a series of replace value steps. But as always, there are multiple and easier ways to achieve the same result. You can watch the full video of this tutorial at the bottom of this blog. In

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Power Query Each Expression: An Introduction

Power Query Each Expression An Introduction - Enterprise DNA

Power Query is a data transformation and manipulation tool that’s available in Microsoft Excel and Power BI. It has a wide range of functions that can be used to transform and manipulate data. In this tutorial, you’ll learn how to use the each expression in Power Query / M Language. You can watch the full

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Remove Empty Columns In Power BI

Remove Empty Columns In Power BI - Enterprise DNA

This blog will demonstrate how to automatically remove all empty columns in Power BI through the Power Query editor. The approach will involve the standard Table.Profile M library function and its additional aggregates parameter to add a non-empty count column. You can watch the full video of this tutorial at the bottom of this blog. Sample Query

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UNION DAX Function Vs Power Query

UNION DAX Function Vs Power Query - Enterprise DNA

In this tutorial, you’ll learn a DAX optimization technique using the UNION function. This tutorial will compare the performance of the UNION function versus Power Query and other techniques for combining tables. The UNION function combines two tables into a single table by combining their rows and removing any duplicate rows. The example in this

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