Back

Speaker "James Casaletto" 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 have profound technical work experience as a leader and individual contributor in a wide variety of internal and customer-facing environments worldwide including startups, academia, government, and large corporations. In addition to being a software developer, I can manage the primary components of a data center, including server hardware, operating systems, application stacks, networks, and storage in clustered and standalone deployments on premise and in the cloud. I have a unique skill set that spans completely from solution requirements through product evangelism and can speak to both technical and business decision makers. Today I'm developing and deploying big data solutions with Apache Hadoop.