{"id":2719,"date":"2018-05-14T00:00:00","date_gmt":"2018-05-14T00:00:00","guid":{"rendered":"https:\/\/azure.microsoft.com\/blog\/enhance-productivity-using-azure-data-factory-visual-tools"},"modified":"2023-05-11T15:39:34","modified_gmt":"2023-05-11T22:39:34","slug":"enhance-productivity-using-azure-data-factory-visual-tools","status":"publish","type":"post","link":"https:\/\/azure.microsoft.com\/en-us\/blog\/enhance-productivity-using-azure-data-factory-visual-tools\/","title":{"rendered":"Enhance productivity using Azure Data Factory Visual Tools"},"content":{"rendered":"<p>With Azure Data Factory (ADF) visual tools, we listened to your feedback and enabled a rich, interactive visual authoring and monitoring experience. It allows you to iteratively create, configure, test, deploy and monitor data integration pipelines without any friction. The main goal of the ADF visual tools is to allow you to be productive with ADF by getting pipelines up and running quickly without requiring to write a single line of code.<\/p>\n<p>We continue to add new features to increase productivity and efficiency for both new and advanced users with intuitive experiences. You can get started by clicking the <strong>Author and Monitor<\/strong> tile in your provisioned v2 data factory blade.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"image\" height=\"425\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/4426a4b3-debf-4d01-b52c-a61dfa1fb2fd.webp\" title=\"image\" width=\"342\"><\/p>\n<p>Check out some of the exciting new features enabled with data factory visual tools since public preview (January 2018):<\/p>\n<h2>Latest data factory updates<\/h2>\n<p>Follow exciting new updates to the data factory service.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 1\" height=\"449\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/f887c075-a3f0-41c4-872c-639cb35fbdf9.webp\" title=\"Enhance 1\" width=\"749\"><\/p>\n<p>View Data Factory deployment region, and resource group. Then, switch to another data factory that you have access to.<\/p>\n<h3><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 2\" height=\"451\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/facf93f5-dad9-48a0-a9af-7308a7a9760c.webp\" title=\"Enhance 2\" width=\"762\"><\/h3>\n<h2>Visual authoring<\/h2>\n<h3>More data connectors<\/h3>\n<p>Ingest data at scale from more than 70 on-premises\/cloud data sources in a serverless fashion.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 4\" height=\"458\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/ce254fce-b967-48a8-836d-cd56db1b4ca4.webp\" title=\"Enhance 4\" width=\"774\"><\/p>\n<h3>New activities in toolbox<\/h3>\n<ul>\n<li><a href=\"https:\/\/azure.microsoft.com\/en-us\/resources\/videos\/azure-friday-ingest-prepare-and-transform-using-azure-databricks-and-data-factory\/\">Notebook<\/a> Activity: Ingest data at scale using more than 70 on-premises\/cloud data sources and prepare\/transform the ingested data in Azure Databricks as a Notebook activity step in data factory pipelines.<\/li>\n<li><a href=\"https:\/\/docs.microsoft.com\/en-us\/azure\/data-factory\/control-flow-filter-activity\">Filter Activity<\/a>: Filter data ingested from more than 70 data sources.<\/li>\n<li><a href=\"https:\/\/docs.microsoft.com\/en-us\/azure\/data-factory\/how-to-invoke-ssis-package-ssis-activity\">Execute SSIS Package<\/a>: Execute SSIS packages on Azure SSIS Integration Runtime in your data factory.<\/li>\n<li><a href=\"https:\/\/docs.microsoft.com\/en-us\/azure\/data-factory\/control-flow-lookup-activity\">Look up Activity<\/a>: Lookup activity now supports retrieving a dataset from any of 70+ ADF-supported data sources. <img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 5\" height=\"464\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/f2f1dad6-73c2-4de3-87e8-e99efcfe8808.webp\" title=\"Enhance 5\" width=\"779\"><\/li>\n<\/ul>\n<h3>Azure Key Vault integration<\/h3>\n<p>Store credentials for your data stores and computes referred in <a href=\"https:\/\/azure.microsoft.com\/en-us\/blog\/secure-credential-management-for-etl-workloads-using-azure-data-factory-and-azure-key-vault\/\">Azure Data Factory pipelines in an Azure Key Vault<\/a>. Simply create Azure Key Vault linked service and refer to the secret stored in the Key vault in your data factory pipelines.<\/p>\n<h3><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 6\" height=\"463\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/3ba9e3ba-336b-4932-889c-152b46ff9b29.webp\" title=\"Enhance 6\" width=\"788\"><\/h3>\n<h3>Iterative development and debugging<\/h3>\n<p><a href=\"https:\/\/azure.microsoft.com\/en-us\/blog\/iteratively-develop-and-debug-your-etl-elt-workflows-using-data-factory\/\">Iteratively develop and debug<\/a> your ETL\/ELT pipelines with data factory visual tools. Perform test runs to debug your pipelines or put breakpoints to debug a portion of your pipeline.<\/p>\n<h3>View test run (debug) status on activity nodes<\/h3>\n<p>You can now view the the last test run status on activity nodes on the pipeline canvas.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 7\" height=\"469\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/91195952-7d8f-4ac1-848a-32dcc5880ffd.webp\" title=\"Enhance 7\" width=\"792\"><\/p>\n<h3>Clone pipelines and activities<\/h3>\n<p>You can now clone an entire pipeline or an activity on the pipeline canvas. This will create an identical copy of the entire pipeline or an activity on the pipeline canvas including the settings.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 8\" height=\"463\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/dcd02522-e1ba-4e8a-9c80-aa0a33c7fa98.webp\" title=\"Enhance 8\" width=\"788\"><\/p>\n<h3>New Resource Explorer actions<\/h3>\n<p>You can now expand\/collapse all the resource explorer entities (pipelines, datasets) with a click of a button. You can also adjust the width of the \u2018Resource Explorer\u2019 by dragging it to the left\/right.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 9\" height=\"469\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/3c4e4871-a806-4025-96a0-f6abaf4bd530.webp\" title=\"Enhance 9\" width=\"782\"><\/p>\n<h3>View\/edit Code for your data factory pipelines<\/h3>\n<p>You can now view and edit JSON for your data factory pipelines. Simply click the \u2018Code\u2019 icon to view your JSON, make edits directly to your JSON and click \u2018Finish.\u2019 You can then \u2018Publish\u2019 your changes to the data factory service.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 10\" height=\"472\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/8372272c-4593-4ef6-8c03-db0bfc8a64ec.webp\" title=\"Enhance 10\" width=\"785\"><\/p>\n<h3>View pending changes to be published to data factory<\/h3>\n<p>Add\/edit\/delete pipelines, triggers, datasets, linked services, integration runtimes and see the number of pending changes to be published to the data factory service.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 11\" height=\"464\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/3ec8eaa0-baad-47a7-abde-fe7ae3682e9d.webp\" title=\"Enhance 11\" width=\"778\"><\/p>\n<h3>Import data factory resources to any branch in your GIT repository<\/h3>\n<p>You can now choose the collaboration branch (generally \u2018master\u2019), create a new branch or use any existing branch to import your data factory resources while setting up the VSTS GIT repository. This is very useful in case you don\u2019t have access to the collaboration branch and want the data factory resources imported in any other develop\/feature branch.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 12\" height=\"460\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/b0ad6891-04a9-4b72-8b0f-75897aecfe4a.webp\" title=\"Enhance 12\" width=\"777\"><\/p>\n<h2>Visual Monitoring<\/h2>\n<h3>Monitor Copy real time progress<\/h3>\n<p>Click the \u2018Details\u2019 icon to view your copy activity continuous progress. Simply click \u2018Refresh\u2019 to get the latest statistics.<\/p>\n<p>\u00a0<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 13\" height=\"300\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/77a99a44-ba94-4792-a30b-19ea94e8603d.webp\" title=\"Enhance 13\" width=\"720\"><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 14\" height=\"390\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/f8c9cff5-8a82-4851-9fa5-97758cfefde6.webp\" title=\"Enhance 14\" width=\"720\"><\/p>\n<h3>Alerts<\/h3>\n<p><a href=\"https:\/\/docs.microsoft.com\/en-us\/azure\/data-factory\/monitor-using-azure-monitor#alerts\">Create alerts<\/a> to be notified on different data factory metrics. For example: pipeline, activity, trigger failure runs. Clicking \u2018Alerts\u2019 will take you to the \u2018Monitor\u2019 tab in azure portal where you can create alerts on data factory metrics.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 15\" height=\"218\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/4a3e73b6-1eff-46ed-9786-8abfbfe22560.webp\" title=\"Enhance 15\" width=\"717\"><\/p>\n<h3>Metrics<\/h3>\n<p>Visualize your <a href=\"https:\/\/docs.microsoft.com\/en-us\/azure\/data-factory\/monitor-using-azure-monitor#metrics\">data factory metrics<\/a> and see the pattern over days, months, and more in a simple graphical interface. Clicking \u2018Metrics\u2019 will take you to the \u2018Monitor\u2019 tab in azure portal where you can visualize your data factory metrics.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 16\" height=\"225\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/873021dc-403d-4751-949c-ab9068472b7d.webp\" title=\"Enhance 16\" width=\"711\"><\/p>\n<h3>View run status of child pipelines<\/h3>\n<p>If your pipeline triggers other child pipelines using \u2018Execute Pipeline\u2019 activity in data factory, you can now view the status of child pipelines from the parent pipeline. Simply click the \u2018Output\u2019 icon under the \u2018Actions\u2019 column and click on the \u2018pipelineRunId\u2019 field.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 17\" height=\"422\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/3c8b92c1-ae1b-4fe5-a46e-53319edc9b45.webp\" title=\"Enhance 17\" width=\"709\"><\/p>\n<h3>Easily copy \u2018runid\u2019 for debugging purpose<\/h3>\n<p>You can now copy the \u2018runid\u2019 of your pipeline, activity runs easily for debugging purposes. Simply select and copy it in case you need to provide it to azure support for debugging purposes.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Enhance 18\" height=\"230\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2018\/05\/4cbab81d-d4b0-4530-afc7-b99055a21aa4.webp\" title=\"Enhance 18\" width=\"708\"><\/p>\n<p>Our goal is to continue adding features and improve the usability of Data Factory tools. <a href=\"https:\/\/docs.microsoft.com\/en-us\/azure\/data-factory\/quickstart-create-data-factory-portal\">Get started building pipelines<\/a> easily and quickly using Azure Data Factory. If you have any feature requests or want to provide feedback, please visit the <a href=\"https:\/\/feedback.azure.com\/forums\/270578-azure-data-factory\">Azure Data Factory forum<\/a>.<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>With Azure Data Factory (ADF) visual tools, we listened to your feedback and enabled a rich, interactive visual authoring and monitoring experience. It allows you to iteratively create, configure, test, deploy and monitor data integration pipelines without any friction.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"ms_queue_id":[],"ep_exclude_from_search":false,"_classifai_error":"","_classifai_text_to_speech_error":"","_alt_title":"","footnotes":"","msx_community_cta_settings":[]},"categories":[1474],"tags":[48],"audience":[3054,3057,3053],"content-type":[],"product":[1821],"tech-community":[],"topic":[],"coauthors":[617],"class_list":["post-2719","post","type-post","status-publish","format-standard","hentry","category-analytics","tag-big-data","audience-business-decision-makers","audience-data-professionals","audience-it-decision-makers","product-azure-data-factory"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Enhance productivity using Azure Data Factory Visual Tools | Microsoft Azure Blog<\/title>\n<meta name=\"description\" content=\"With Azure Data Factory (ADF) visual tools, we listened to your feedback and enabled a rich, interactive visual authoring and monitoring experience. 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