Just a few weeks ago, we announced the public preview of the new browser-based UI for Azure Data Factory. See Gaurav’s blog here detailing the release. To help you understand how to build complex data integration projects in the ADF Visual Design interface, we’ve partnered with Pragmatic Works, who have been long-time experts in the Microsoft data integration and ETL space, to create a new set of hands-on labs that you can now use to learn how to build those DI patterns using ADF V2.
That link points to a GitHub repo for the lab, where you will find data files and scripts in the Deployment folder. There are lab manual folders for each Lab and overview presentations, shown below for more details. You will also find a series of PowerShell and DB scripts as well as ARM templates that will generate resource groups that the labs need in order for you to successfully build out an end-to-end scenario with sample data that you can use for Power BI reports in the final Lab 9. Here is how the individual labs are divided:
- Lab 1 – Setting up ADF and Resources, Start here to get all of the ARM resource groups and database backup files loaded properly.
- Lab 2 – Lift and Shift of SSIS to Azure, Go to this lab if you have existing SSIS packages on-prem that you’d like to migrate directly to the cloud using the ADF SSIS-IR capability.
- Lab 3 – Rebuilding an existing SSIS job as an ADF pipeline.
- Lab 4 – Take the new ADF pipeline and enhance it with data from Cloud Sources.
- Lab 5 – Modernize the DW pipeline by transforming Big Data with HDInsight.
- Lab 6 – Go to this lab to learn how to create copy workflows in ADF into Azure SQL Data Warehouse.
- Lab 7 – Build a trigger-based schedule for your new ADF pipeline.
- Lab 8 – You’ve operationalized your pipeline based on a schedule. Now learn how to monitor and manage that DI process.
- Lab 9 – Bringing it all Together