Azure Stream Analytics is a fully managed low latency stream processing service that takes the complexity out of stream processing by providing a SQL-like language for expressing data transformations and analysis.
Stream Analytics enables you to harness the power of the cloud to easily create, scale, manage your stream processing solution.
It enables you to create live dashboards, notifications etc. on data in motion within minutes, not days. All you have to do is write your stream processing logic in a SQL like language.
In this session learn details on built-in language capabilities such as filtering, temporal semantics with windowing functions, joining multiple streams, using static data with streaming data etc.
Additionally learn how Stream Analytics integrates with other services such as Azure Event Hubs, Azure Machine Learning, Azure SQL DB, Azure Blobs, Power BI etc. to create your end to end real time solution. Walk out with the knowledge to create your first stream processing job.
See some live demos of end to end stream processing solutions to help give you an idea what is possible when you unlock insights from your data in real-time.
Ryan CrawCour is a Senior Program Manager from the Azure Stream Analytics team. He is a data veteran having spent the past 20+ years dealing with all sorts of data at rest in a variety of different database platforms from SQL, to NoSQL, Relational to Document to Graph, he has recently shifted focus to explore the world of new opportunities available through data in motion.
Paco Gonzalez — Big Data Virtual Chapter Leader