AWS Tutorials - Using AWS Glue DataBrew in JupyterLab

AWS Tutorials for AWS glue DataBrew - • AWS Tutorials - Workin...
DataBew Integration with JupyerLab on local machine - docs.aws.amazon.com/databrew/...
DataBew Integration with SageMaker Notebook JupyerLab - github.com/aws/aws-glue-datab...
AWS Glue DataBrew is a visual data preparation tool that enables users to clean and normalize data without writing any code. JupyterLab is an interactive development environment for notebooks, code, and data. It allows users to configure and arrange workflows in data science and computing. Integrating DataBrew and JupyterLab enhances productivity and experience as users can work with DataBrew right from the JupyterLab interface.

[@YghorCastello]

I have a notebook that was used to do a job via glue, I need to know how to activate the Job bookmark and how to create a schedule for it. Do you have a video that shows this step by step?

[@AWSTutorialsOnline]

I have two videos about job book mark - please check my channel

[@ratnasravyasajja9735]

Very Informative.. Can we apply some custom data quality rules in databrew through writing code from sagemaker?

[@AWSTutorialsOnline]

You mean custom rule created by using code?

[@ratnasravyasajja9735]

@@AWSTutorialsOnline yes, using code for custom rule. Is it possible for databrew?

[@AWSTutorialsOnline]

@@ratnasravyasajja9735 Hi. Data quality checks are fixed. You cannot create a custom check using code.