DataStage in Cloud Pak for Data is a data integration offering for designing and running data flows that move and transform data.

Create a simple parallel job

This videos shows you how to create a simple data transformation job in IBM Cloud Pak for Data.

Create a job from a template - Db2 source and target

This video shows you how to create a data transformation job based on a template to move data between Db2 instances in IBM Cloud Pak for Data.

Create a job from a template - Local file source and remote directory target

This video shows you how to create a data transformation job based on a template to move data from a local file to a remote directory in IBM Cloud Pak for Data.

Create a job from a template - Remote directory source and target

This video shows you how to create a data transformation job based on a template to move both a single file and multiple files using wildcards between remote directories in IBM Cloud Pak for Data.

DataStage connectors and stages

This playlist contains short videos showing you how to use the most common DataStage connectors and stages.

Auto Scaling with DataStage

Auto scaling helps to automatically distribute workloads. This video shows how IBM DataStage will elastically spin up or scale down compute instances as needed.

Improve Data Quality

Poor quality of data can seriously harm your business. It can lead to bad analysis, or even worse, bad business decisions. In this video, you will see how you can improve the quality of your data right in your web browser with IBM DataStage Flow Designer. While this video show the DataStage Flow Designer, this can also be accomplished in Cloud Pak for Data.

Boost developer productivity with machine learning

Machine learning makes it easier to perform data integration, quality, and governance on IBM DataStage Flow Designer. In this video, you'll see how DataStage developers can leverage the job clustering, smart palette, and stage suggestions features to help them build jobs. While this video show the DataStage Flow Designer, this can also be accomplished in Cloud Pak for Data.

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