Streaming Analytics and Machine Learning with DataTorrent Apoxi (TM)
jeu. 26 avril à 17:00
Traditionally, stream processing applications for big data have not incorporated machine learning. Machine learning has been more closely aligned with batch processing approaches. However, this is changing as demand builds for the convergence of stream processing with machine learning. The stream processing market has matured with a number of good engines such as Apex, Flink, and others. Kafka has established itself as a de-facto messaging platform to use with streaming engines. Second ML libraries such as Spark MLLib, which is a leader in ML processing for big data, can be used in streaming mode. As a result, there is growing interest in applying ML to common, everyday problems, not just academic or deeply specialized use cases. To accomplish this, there is a need for a general purpose framework and platform that will allow these technologies to come together. DataTorrent’s Apoxi is a technology that has been developed to do just this. To start with, it combines best of breed technologies such as Spark ML, Apex Streaming, Kafka Messaging, Drools complex event processing and Druid OLAP to create a single unified platform that can solve complex business problems with big data and data-in-motion. It enables application developers to focus on business outcomes and not technical or engineering problems. In this webinar, we will introduce Apoxi and look at a real-world example application that was built on it. We will demo the app, show how it works and see how it delivers more impactful business outcomes. Presenter:
Pramod Immaneni, Chief Architect at DataTorrent Please register for the webinar at: http://bit.ly/2vp5j5g After registering, you will receive a confirmation email containing information about joining the webinar. Reduce time to market and total cost of ownership with DataTorrent's AppFactory -
www.datatorrent.com/appfactory Brought to you by DataTorrent - www.datatorrent.com
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