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Lehigh Valley, PA /

Big Data from Little Things: Consuming and Processing Streaming Data from IoT

Ben Franklin Tech Ventures 116 Research Drive , Bethlehem, PA 18015 (map)

This month is all about big data from little things. Paul and Tom will show how they used open source tools to model and learn from data streamed from IoT devices. If you're interested in big data, machine learning, or leveraging data from multiple sensors and devices - this is the meetup for you.


- 6:30pm - Food / Networking

- 7:00pm - Best Mode Quotient - Edge to AI

- 8:30pm - Q&A / Wrap-up

Best Mode Quotient - Edge to AI

Perceived fatigue has been established to be an important part of performance prediction and injury prevention for athletes. Using open source technology, we set out to try and model perceived amount of fatigue (a.k.a. Best Mode Quotient) using data from IoT devices and launching ephemeral machine learning models in the cloud.

Cloudera and Hortonworks have recently merged to create an open source leader that combines the best-of-breed big data technologies in the data flow, machine learning and AI space. During this meetup, you will learn how to leverage Cloudera’s suite of tools (Nifi, Spark, CDSW and Cloudbreak) for Edge to AI hybrid infrastructures.

Speakers: Paul has been playing with large amounts of data since the beginning of his career in France. Local resident of Philadelphia since 2008, he was always interested in learning about the latest technologies and their implications in our daily lives. With this technical expertise, he worked as an architect and technology evangelist for companies big and small. He now is a part of the Solution Engineering team at Cloudera and leads the Future of Data group in Philadelphia.

Tom has been working with data for almost 20 years. He is currently a Solutions Engineer with Cloudera and works with some of the largest companies in the world who value data as a strategic asset. Many of those organizations have data footprints in the petabyte and exabyte scale while also having to leverage that data in near real-time to drive decision making and actionable intelligence. Tom assists these organizations with not only their data strategy and architecture, but also in how they leverage open source technology to perform machine learning and artificial intelligence. Tom currently resides in the Lehigh Valley.


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