Introducing Azure Stream Analytics: Processing on Near-Realtime Data

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Description

Vast amounts of data are flowing at high velocity over the wire today. Organizations that can process and act on this data in real time can dramatically improve efficiencies and differentiate themselves in the market. Scenarios of real-time stream analytics can be found across all industries: personalized real-time stock trading analysis and alerts offered by financial services companies; real-time fraud detection; data and identity protection services; reliably ingesting and analyzing data generated by sensors and actuators embedded in physical objects (IoT); web click stream analytics; and CRM applications issuing alerts when customer experience within a time frame is degraded. Businesses are looking for the most flexible, reliable, and cost effective way to do such real-time event stream data analysis to succeed in the highly competitive modern business world. Come learn about Microsoft Azure Stream Analytics, a fully managed real-time stream computation service hosted in Microsoft Azure, that provides highly resilient, low latency, and scalable complex event processing of streaming data. Azure Stream Analytics enables developers to easily combine streams of data – such as click-streams, logs, metering data or device-generated events – with historic records or reference data to derive business insights easily and quickly. Integrated with Azure Event Hub for easy ingestion, and Azure Storage and Azure Database for easy consumption, Azure Stream Analytics pipelines can power dashboards, detect anomalous conditions, as well as drive real-time decisions.

Tag:

Big Data

Day:

2

Session Type:

Breakout

Code:

DBI-B316

Room:

Hall 8.0 Room F1

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