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Building Dynamic Pipelines in Azure Data Factory v2

Building Dynamic Pipelines in Azure Data Factory v2

with Mitchell PearsonIn case you’re not aware, Azure Data Factory v2 has now been generally released. In a recent webinar, hosted by Mitchell Pearson, he discussed building dynamic pipelines in Azure Data Factory v2.

In this webinar a basic understanding of Azure and ETL is useful, as he will not be discussing how to set up and provision Azure Data Factory. We did have a webinar hosted by Microsoft Architect Brad Schacht a few months ago that will give you an overview of Azure Data Factory V2 and get you ready to orchestrate data movement with Azure Data Factory like a pro.

Michell covers Azure Data Factory v2 in this webinar, which now has a drag and drop user interface that makes it significantly easier to build out your ETL processes.  He’ll start with teaching some navigation in ADF v2, along with a demo, and the actions you have available: create pipelines, copy data, configure SSIS integration runtime and set up your code repository.

He will also cover how to use the various activities available in Azure Data Factory with demos included for each. And as a bonus, he’ll discuss and demo how to use input and output parameters to make the pipeline dynamic. Click here to view Mitchell’s slides from the webinar.

So, if you’re getting started with Azure Data Factory v2 or want to learn more about it and how this new version can help you with ETL, this free one-hour webinar is a great place to learn. Watch the full webinar below. 

Mitchell currently has a series of six posts on his blog dedicated to Azure Data Factory. Be sure to check out his blog at mitchellpearson.com to view these blogs, as well as additional Azure Data Factory blogs he adds to stay up to date.

We offer free webinars every Tuesday at 11 am EST – check out the upcoming schedule on our website. Need more training? Our On-Demand Learning platform has 55+ (and growing) courses taught by industry experts covering Business Intelligence, Azure, Big Data, Business Analytics and more.

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