Adf automatic file distribution

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An impressive scanning speed of 30 doublesided pages per minute and an Automatic Document Feeder that holds up to 20 sheets means you can reliably scan whatever you like in no time at all - quickly getting you back to the more important things in your life. Custom file tagging With custom file tagging you can add your own tags to scanned document files with minimal fuss — making it easier and faster for you to search for, find and retrieve them at a later date.

Intuitive ScanSnap Home software The intuitive ScanSnap Home software included helps quickly and easily convert the papers you have into the digital files you need, giving you greater control, and helping you focus on what matters most. From automatic classification according to document type, image optimisation and final file distribution, to assisting you to manage and edit scanned data from documents, receipts, business cards, photos, and more, ScanSnap Home takes the stress out of organising and finding what you need.

Lastly, I am interested in exploring an option that will allow me to use store procedures on the SQL DW to drop and create my curated tables.

The pipeline design will be very similar to my previous pipelines by starting with a lookup and then flowing into a ForEach activity. The success and fail stored procedures simply log the status of the pipeline run in the pipeline parameter table. Additionally, the destination name and schema have been defined as stored procedure parameters and are being passed to the stored procedure. In a scenario where I am interested in renaming the original curated table, rather than dropping the original curated table, I would use this script:.

Lastly, it is important to note that within SQL DW, if I am attempting to drop or rename a table that has dependencies linked to Materialized View that has been created, then the drop and rename script will fail. Related Articles. Azure Data Factory Pipeline Variables. Select the repository where you want to save your pipeline YAML script.

We recommend saving it in a build folder in the same repository of your Data Factory resources. Ensure there's a package. Select Starter pipeline. If you've uploaded or merged the YAML file, as shown in the following example, you can also point directly at that and edit it. Learn more information about continuous integration and delivery in Data Factory: Continuous integration and delivery in Azure Data Factory. Skip to main content. This browser is no longer supported.

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Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type. Showing results for. Show only Search instead for. Did you mean:. Sign In. Mark Kromer. Published Nov 22 AM 8, Views. Tags: Azure Data Factory.