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Accelerate Decision Making with Real-Time Analytics on AWS

The number of sources generating continuous, streaming data has exploded in recent years. From website clickstream data to telemetry data from Internet of Things (IoT) devices, the variety, volume, and velocity of data continues to increase. In response, businesses are evolving their analytics approach from batch to real time, and turning to new tools to deliver actionable insights in seconds instead of hours or days. With AWS, you can easily and cost-effectively collect, process, and analyze real-time streaming data at any scale, so you can learn what your applications and customers are doing right now—and respond immediately.

In this webinar, you’ll learn about AWS real-time analytic solutions, including Amazon Kinesis Data Streams, Kinesis Data Firehose, and Kinesis Data Analytics. You’ll also hear about real-time solutions from APN Partners, Databricks, MemSQL, and Zoomdata that complement or integrate with Amazon Kinesis services.

Join us to:
  • Learn how your organization can leverage real-time streaming analytics to capitalize on time-sensitive opportunities, meet customer demands, and reduce operational risks
  • Understand best practices for tackling the architectural and business challenges of transitioning from batch to real-time analytics
  • Hear how real-time analytics have already benefited AWS customers, Viacom and Infiswift
  • Find out how to get started with Amazon Kinesis and APN Partner solutions from Databricks, MemSQL, and Zoomdata
When: Available On Demand (please register to view)

Who Should Attend:
Data Engineers, Data Scientists, Data Analysts, Chief Architects, VPs of Engineering, VPs of Analytics, IT Directors, CTOs, Director-level business decision-makers

AWS Speaker: Ryan Nienhuis; Sr Product Manager, Amazon Kinesis
Databricks Speaker: Brian Dirking; Sr Director of Partner Marketing
MemSQL Speaker: Mike Boyarski; Sr Director Product Marketing
Zoomdata Speaker: Samuel Diener; Sr Director Strategic Accounts and Technology