In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
RR
Labs are keeping up-to-date, but are lacking overall theoretical summary to teach symmatically how each code could work. Still a very typical problem of courses offered by Google Cloud.
RT
Good intermediate course covering the big picture about how to develop data platforms using GCP and Dataflow.
Showing: 10 of 10
A lot labs with problem and the responsable for support (QWIKLABS) doesn't help.
Labs are keeping up-to-date, but are lacking overall theoretical summary to teach symmatically how each code could work. Still a very typical problem of courses offered by Google Cloud.
Good intermediate course covering the big picture about how to develop data platforms using GCP and Dataflow.
In-depth, Practical learning through labs.
very useful
Some of the labs were buggy but suppurt not really willing to help.
There are many errors in the labs
* Some instruction of lab is not clear or insufficient to complete.
* The speaking of instructors is also not clear. Even the transcript is also incorrect (maybe speechToText). Difficult to follow.
He tenido que repetir varios Labs porque no detectaban los últimos checks
i need to fix completion issue of this course . there is issue