Data Transformation


Support for Machine Learning Studio (classic) will end on 31 August 2024. We recommend you transition to Azure Machine Learning by that date.

Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources.

ML Studio (classic) documentation is being retired and may not be updated in the future.

This article lists the modules that are provided in Machine Learning Studio (classic) for data transformation. For machine learning, data transformation entails some very general tasks, such as joining datasets or changing column names. But, it also includes many tasks that are specific to machine learning, such as normalization, binning and grouping, and inference of missing values.


Applies to: Machine Learning Studio (classic) only

Similar drag-and-drop modules are available in Azure Machine Learning designer.


Data that you use in Machine Learning Studio (classic) is generally expected to be "tidy" before you import it to Machine Learning Studio (classic). Data preparation might include, for example, ensuring that the data uses the correct encoding and checking that the data has a consistent schema.

Modules for data transformation are grouped into the following task-based categories:

List of modules

The following module categories are included in the Data Transformation category:

See also