Data preparation is key to becoming a successful data analyst. You’ll learn how to do essential data preparation steps such as filtering and renaming columns and how to use data preview in Power BI to identify common errors that appear in datasets.

Introduction to Power Query

What is clean data?

Introduction to Power Query demo

Load data and promote headers

Rename and reorder columns

Changing data types

Profiling your Data and Introduction to Power Query

In this chapter, you will learn about the key data preview features available through Power Query and how they can help you summarize the characteristics of your dataset. You’ll also understand how investigating your dataset in Power Query can assist in determining the data transformation steps you need to take. 

Data preview features in Power Query

Options

Column Distribution

Column Quality

Column Profile

Data preview differences

Data preview features

Column distribution and duplicates

Column quality and missing values

Column profile

Profiling to find anomalies

Data Preview features in Power Query

The preparation and transformation of text data can also be carried out through Power Query. Through interactive exercises, you’ll learn about some of the most common text transformations, such as how to split and merge text columns, trim unwanted characters from any text data, and prefixes to any text data in your dataset.

Transforming text in Power Query

Universally-applicable transformations

Text transformation

Trim & clean

Merge & extract length

Split & add prefix

Data Manipulation

This chapter covers the most common numerical transformations you’ll use in Power Query. You’ll learn how to perform some more advanced Power Query transformations. This includes applying logarithmic and square root transformations on numerical columns, rounding numerical data, and extracting month and week names from date columns.

Numerical transformations in Power Query

Numerical vs. Date transformations

Numerical transformations

Absolute value and rounding

Multiplication, addition, and square root

Date transformations

Congratulations!

Exercises and Datasets

Course Glossary

In this interactive Power BI course, you’ll learn how to use Power Query Editor to transform and shape your data to be ready for analysis. You’ll also get to grips with various text and numerical transformations, including multiplication, rounding, and split and merge text columns, to help you become even more efficient in data preparation.

<h2>Learn How to Use Power Query Editor </h2>
Transform and shape your data in Power BI. In just 3 hours, you’ll cover essential data preparation steps, previewing data in power query, and transformations. 
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By the end of this course, you’ll feel confident using a range of Power Query Editor tools and techniques and know how to clean and prepare your data for the next stage in the data analysis workflow.
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<h2>Manipulate Data in Power BI </h2>
Power Query is a powerful data manipulation framework available throughout a number of Microsoft tools, which allows you to clean different data types ready for analysis. You’ll learn how to deal with duplicates, missing values, and profiling to find anomalies. After each new topic is introduced, you'll have the opportunity to put your new knowledge into practice with hands-on exercises, such as splitting and merging text columns. 
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<h2>Master Data Transformation in Power Query</h2>
The last two chapters of this course are focused on helping you with transformations in Power BI, allowing you to transform text, apply logarithmic and square root transformations, and date transformations. 
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This course is part of the Data Analyst and Power BI tracks, offering you plenty of ways to improve your Power BI skills or even build towards a career in data analysis. 

Introduction to Power BI

Learn how to use Power Query Editor in Power BI to transform and shape your data for analysis. Plus, get to grips with numerical transformations in Power BI.

Data Preparation Course in Power BI with Power Query Editor | DataCamp 

In this interactive Power BI course, you’ll learn how to use Power Query Editor to transform and shape your data to be ready for analysis.

Data Preparation in Power BI

Veri Analisti Power BI'da

Power BI Temelleri

Check all your columns for missing values.

View the mean, standard deviation, minimum, and maximum for one column.

View the detailed distribution of one column.

Data preview differences

Data Preparation in Power BI

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