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.
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.
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.
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.