How to Execute ETL Process in Power BI — Data Analysis in Power BI — Chapter 4
Data transformation helps to clean, pivot, transpose, merge and prepare model-ready data.
For any data analysis project, we are following CRISP-DM (Cross-industry standard process for data mining) framework.
In this framework, data processing ( data transformation) is one of the key steps to start with the project.
In previous blogs of this series (Data Analysis in Power BI), we get an idea of how to do data profiling using Power BI.
In this blog, we are going to understand how to transform data using different cleaning, shaping and combining methods of Power BI mainly Power Query Editor.
In-built ETL features of Power BI
Power BI consists of a powerful ETL tool which is known as Power Query Editor. It helps to perform different transformations to the data. It uses a programming language named “M” (mashup).
Data Cleaning and Evaluation
To start with, you need to first clean the data using different methodologies of Power Query Editor and perform the evaluation on the column data type.
