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Identifying the Root Cause

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Course Introduction
Troubleshooting in Power Query
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Overview
Difficulty
Intermediate
Duration
40m
Students
57
Ratings
5/5
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Description

In this course, we’ll review the Power BI Desktop interface. Then, we’ll show you how to load data into Power BI Desktop and how to save your file. We will also explain data profiling and look at the various data profiling options in Power Query like column quality, column value distribution and column profiling, and the benefits of using these.  

Lastly, we will look at how to resolve cell-level errors, empties, and inconsistencies in Power Query. This section will cover how to replace errors, replace values, remove rows, and how to identify the root cause of the error using Power Query. The demos in this course will provide you with practical examples that will help you to troubleshoot when encountering issues while loading data into Power BI.

Learning Objectives

  • Understand how to load data into Power BI and how to optimise functionality and size by using data profiling
  • Understand how to resolve errors, empties, and data inconsistencies in Power Query

Intended Audience

  • Anyone who would like to learn about importing data into Power BI
  • Anyone who needs to resolve cell-level errors or empties in a Power BI model or who would like to understand data profiling to improve the functionality of their model

Prerequisites

  • Some basic knowledge of, or experience in, working with large datasets
  • Some experience with Power BI (not mandatory)

Resources

The files used in this course can be found in the following GitHub repo: https://github.com/cloudacademy/loading-data-power-bi 

Transcript

The third option is to identify the root cause of the error. To show you this, I will return to an example I saved as PowerBIError.pbix, if you want to follow along. This was the example where we had replaced some of the values in the product ID column to include the letter K. This resulted in three errors in this column. In power query view, if column quality is selected, you can see there are three errors in this column. Error values don't prevent queries from loading, but the error values are loaded as blank values. You can check the error message behind the error by selecting the error cell. The error message will then show in the preview section at the bottom. In this case, it states, could not be converted to number. The error happens because Power Query is trying to convert the product IDs, that include letters, into numbers, as this is currently a numbers column. Therefore, the numbers column must be changed to text type. Right click the product ID column. Select change type to text. Select replace current. Error messages no longer appear in the product ID column.

About the Author
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Bianca Burger
Chartered Accountant and Finance Business Partner
Students
57
Courses
1

Bianca is a chartered accountant and finance business partner who works with Power BI regularly to create useful, interactive dashboards to analyze financial metrics.  She has worked as a lecturer and as a financial analyst in FMCG companies assisting sales and marketing teams with reviewing and understanding their financial results and forecasts, and identifying risks and opportunities for improvement.  Bianca enjoys using technology to automate and simplify financial metrics.