Back

Speaker "Sunil Patil" Details Back

 

Topic

Building and Deploying Predictive Models for Real-time IoT Solutions

Abstract

Predictive analytics has matured as a core enterprise practice required for creating and maintaining competitive advantage. Today, this technology enables organizations to leverage historical data to not only predict future events, but also to gain understanding and wisdom about their core business. The Internet of Things is here. Sensors, mobile devices, and other networked systems are creating, sending, and collecting large volumes of data. The IoT is poised to change almost every aspect of how industries do business, and one of those aspects is using predictive analytics. Predictive analytics based on real-time data is already being used today in manufacturing, oil and gas, energy, security, health care, insurance, and a number of other industries. Practitioners are finding that the existing platforms and tools do not scale to handle the volume, velocity, and variety of data they wish to analyze. This presentation will discuss cutting edge tools and platforms for producing, consuming, and analyzing real-time message sources of big data for the purpose of predicting future events.

Profile

I am a big data technology specialist, who excels in architecting and developing Big data solutions to meet enterprise business needs. I always enjoy learning new applications and methodologies that can help my customers. Current areas of expertise include, Apache Spark, Apache Hadoop, Apache Kafka, Elasticsearch, LogStash, Kibana, Hive, Flume, Sqoop, Play Framework, Angular, BootStrap, Scala, DeployR, Hue, WebHDFS, YARN, TEZ, Oozie, ZooKeeper