Abstract: 

The demo will consist of analyzing mobile packet data collected over a month and a half span comprising of 500M records. We will be leveraging OmniSci Immerse to gain interactive analytics both over space and time. Then we will demonstrate how OmniSci’s JupyterHub integration can be leveraged to quickly and easily bring data into python. Finally we will leverage Ibis to interact with OmniSci and leverage a machine learning model to forecast some data.

Bio: 

Joe is a Solutions Engineer at OmniSci with a focus on Data Science. Previously he was at Ford Motor Company on their Autonomous Vehicle team where he was responsible for mass decoding efforts and aiding in design for their data lake and Apache Spark processing architecture. After that he was part of the team tasked with developing the algorithm for Ford’s BlueCruise road classification system. Joe has over 4 years of experience in the Data Science and Data Engineering space and over 10 years of experience in various aspects of IT.