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 BPower 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.
In the below video, you will find the step by step process with examples. Let’s get your hands dirty.
Data Shaping ( Pivot, Unpivot, Transpose etc.)
In some of the data analysis projects, data shaping plays a key role to transform the data for the next level.
In the below video, you will get an idea of how you can implement pivot, unpivot, transpose etc.
Data Combining ( Merging, Appending etc.)
Now you will learn, how you can build relationships in Power Query Editor.
In many data analysis projects, I used these merge, append queries techniques.
Let’s check the below video, you will find detailed practical examples.
In this blog, you learn about below things
- What is Power Query Editor
- Data Cleaning and Evaluation
- Data Shaping — Pivot, Unpivot, Transpose
- Data Combining — Merging, Append, Expand, Aggregate
In my next blog, we will learn more in detail.
If you have any questions related to this project, please feel free to post your comments.
Please visit my website for other technical resources.
Please like, comment and subscribe to my YouTube channel which you have already seen. 🙂 Keep Learning.