Courses
Data Preparation in Power BI
基本的技能水平
更新 2025年12月Power BIData Preparation3小时9 videos26 Exercises2,050 XP81,936成就声明
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试试DataCamp for Business课程描述
Learn How to Use Power Query Editor
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.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.
Manipulate Data in Power BI
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.Master Data Transformation in Power Query
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.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.
先决条件
Introduction to Power BI1
Profiling your Data and Introduction to Power Query
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.
2
Data Preview features in 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.
3
Data Manipulation
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.
4
Numerical transformations in Power Query
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.