@javier Thanks for the question, When designing a pipeline in Azure ML Designer, each step or module creates intermediate datasets that can be seen using the UI. Those datasets are persisted in the blob storage. To filter data, you can use Apply SQL Transformation to write SQL query or Split Data using regular expression. You can also use Execute Python Script and Execute R script module to write your own data processing logic.
Designer Pipeline Documentation:https://github.com/Azure/AzureMachineLearningGallery/blob/main/pipelines/README.md