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Visual Studio>Tools>Microsoft Azure DataFactory Tools for Visual Studio 2015
Microsoft Azure DataFactory Tools for Visual Studio 2015

Microsoft Azure DataFactory Tools for Visual Studio 2015

AzureDataFactory

|
283,969 installs
| (19) | Free
An integrated development environment for Data Factory application development.
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We are glad to announce the Visual Studio plugin for Azure Data Factory. With this release, customers can interactively author and deploy data pipelines using the rich Visual Studio interface.

Our goal is to simplify the Azure Data Factory authoring experience and remove on-boarding and deployment challenges. The Azure Data Factory plugin in Visual Studio improves productivity and efficiency for both new and advanced users with tailored experiences and rich tooling.

Features enabled in this milestone

  • Template based authoring: Select use-cased based templates, data movement templates or data processing templates to deploy an end-to-end data integration solution and get started hands-on quickly with Data Factory.
  • Integration with Solution Explorer for authoring and deploying Data Factory entities: Create & deploy pipelines and related entities as Visual Studio projects.
  • Integration with Diagram view for visual interaction while authoring: Visually author pipelines and datasets with aid from the Diagram view.
  • Integration with Server explorer for browsing and interaction with already deployed entities: Leverage the Server Explorer to browse already deployed data factories and corresponding entities. Import a deployed data factory or any entity (Pipeline, Linked Service, Datasets) into your project.
  • JSON editing with schema validation and rich intellisense: Efficiently configure and edit JSON documents of Data Factory entities with rich intellisense and schema validation

Details

  • Data Factory Templates
    • Create data integration solution based on a template 
      • ‘Include sample data’ configures the solution with sample data enabling you to deploy the data integration workflow with minimal configuration and see it up and running quickly
    • Follow instructions, configure and create resources
    • Publish to the data factory
  • Empty Data Factory Project
    • Start with the empty canvas, create pipelines and related entities
    • Publish to the data factory
  •  Solution Explorer
    • Add New data Factory entities (Pipelines, Linked Services, Datasets) from templates
      • Gesture: Right click and add
    • Open existing entities from the solution explorer in the Document (Canvas)
      • Gesture: select and double click
    • Reference Hive projects in the Data Factory solution
      • .hql files automatically uploaded to the Azure BlobStore location based on the activity configuration
  • Server explorer
    • Browse deployed data factories and corresponding entities o Gesture: Click Azure SDK and open Data Factory node
    • Open deployed entities
      • Gesture: Select and double click
    • Export to the project
      • Gesture: Select entity, right click, click ‘Export to Project’
  • Canvas
    • Configure JSON files
      • Gesture for intellisense: hit space after the quote
    • View pipeline diagram
      • Gesture: Select pipeline from the solution explorer and open
  • Build
    • Build the solution or the project to identify issues
      • Gesture: Right click on the project/solution, click ‘build’
  • Publish
    • Deploy the pipeline and related entities to a data factory
      • Gesture: Click ‘Publish’ on the tool bar to deploy to the selected data factory
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