Azure Stream Analytics<\/span><\/b><\/p>\n Azure Stream Analytics<\/a> is a real-time analytics and complex event-processing engine designed to analyze and process high volumes of fast streaming data from multiple sources simultaneously. Use Stream Analytics to build an end-to-end serverless streaming pipeline with just a few clicks. Go from zero to production in minutes using SQL\u2014 it\u2019s easily extensible with custom code and built-in machine learning capabilities for more advanced scenarios.<\/p>\n Example use cases for Stream Analytics:<\/p>\n This image illustrates how image shows how data is sent to Stream Analytics, analyzed, and sent for other actions like storage or presentation.<\/span><\/em><\/p>\n Stream Analytics Resources:<\/strong><\/p>\n Azure Data Explorer<\/span><\/b><\/p>\n Azure Data Explorer<\/a> is a fast, fully managed data analytics service for real-time analysis on large volumes of data streaming from applications, websites, IoT devices, and more. Ask questions and iteratively explore data on the fly to improve products, enhance customer experiences, monitor devices, and boost operations. <\/span><\/p>\n Either Azure Stream Analytics or Azure Data Explorer can be used for real-time analytics and detection<\/a> as illustrated in the diagram above.<\/span><\/em><\/p>\n Data Explorer Resources<\/span><\/b><\/p>\n Azure Data Factory<\/span><\/b><\/p>\n Big data requires service that can orchestrate and operationalize processes to refine these enormous stores of raw data into actionable business insights. Azure Data Factory<\/a> is a managed cloud service for these complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects. It\u2019s built for all data integration needs and skill levels.<\/p>\n Easily construct ETL and ELT processes code-free within the intuitive visual environment or write your own code. Visually integrate data sources using more than 90+ natively built and maintenance-free connectors at no added cost. Focus on your data\u2014the serverless integration service does the rest.<\/p>\n This solution architecture for anomaly detection in real-time data streams<\/a> offers an easy ‘Try it Now’ experience with options for customized data.<\/em><\/span><\/p>\n Data Factory resources<\/strong><\/p>\n More videos on analytics in Azure Government<\/span><\/b><\/p>\n Azure Government YouTube channel<\/span><\/b>:<\/span><\/p>\n \u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" Azure Government continues to invest in delivering new cloud capabilities to government customers at a rapid pace. Over the next few weeks, we\u2019ll highlight a wide range of new services along with how-to resources to help you accelerate modernization initiatives. New analytics services available in Azure Government include Azure Stream Analytics, Azure Data Explorer, and […]<\/p>\n","protected":false},"author":1804,"featured_media":19058,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2],"tags":[50,95,141,184],"class_list":["post-19057","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-announcements","tag-analytics","tag-azure-government","tag-blueprint","tag-cloud-strategy"],"acf":[],"blog_post_summary":" Azure Government continues to invest in delivering new cloud capabilities to government customers at a rapid pace. Over the next few weeks, we\u2019ll highlight a wide range of new services along with how-to resources to help you accelerate modernization initiatives. New analytics services available in Azure Government include Azure Stream Analytics, Azure Data Explorer, and […]<\/p>\n","_links":{"self":[{"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/posts\/19057","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/users\/1804"}],"replies":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/comments?post=19057"}],"version-history":[{"count":0,"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/posts\/19057\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/media\/19058"}],"wp:attachment":[{"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/media?parent=19057"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/categories?post=19057"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/azuregov\/wp-json\/wp\/v2\/tags?post=19057"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
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