Abstract: As Organizations are looking to transform into data driven organizations. Stream analytics has emerged as an integral part of Enterprise Data platform architectures along with batch ETL. Stream analytics help to gain maximum value from user-interaction events, applications and machine logs. Ingesting, processing, and analyzing these data streams quickly and efficiently is critical in fraud detection, click stream analysis, sentiment analytics, online recommendations and IOT Scenarios among many examples. In this session we will look at options available in azure for real-time analytics and deep dive into Azure Stream Analytics. Build streaming jobs that can blend and aggregate data as it arrives to drive live Power BI dashboards. Plus, we’ll explore how a complete lambda architecture can be created when combining stream and batch data together and finally how it integrates with Azure ML.

Speaker Bio: Sriharsh Adari is a technology strategist and Cloud BI Architect. He has around 16 years of experience helping customers with setting up Data Platforms focused on Microsoft BI. He has helped multiple global customers across different industry verticals set up enterprise data platforms using the Microsoft Data Platform and Business Intelligence stack. Over the past few years, he has been helping customers migrate on-premise data workloads onto Cloud Data Platforms – Azure, AWS, and set up new data platforms on cloud. Sriharsh is passionate about all things related to data, big data and Business Intelligence.