Edge to AI: Analytics from Edge to Cloud with Efficient Movement of Machine Data

Edge to AI: Analytics from Edge to Cloud with Efficient Movement of Machine Data

Thursday, March 21
2:00 PM - 2:40 PM
Room 129-130

In this talk, we will walk you through the simple steps to build and deploy machine learning for sentiment analysis and YOLO object detection as part of an IoT application that starts from devices collecting sensor data and camera images with MiNiFi. This data is streamed to Apache NiFi which integrates with Cloudera Data Science Workbench for classification with models in real-time as part of the real-time event stream. We parse, filter, fork, sort, query with SQL, dissect, enrich, transform, join and aggregate data as it is ingested.

The data is landed in a Cloudera data store in the cloud for batch and interactive analytics with Spark, Hive, Phoenix, HBase, Druid, Kudu and Impala.


Presentation Video


Timothy Spann
Field Engineer, Data in Motion
Tim Spann was a Senior Solutions Architect at AirisData working with Apache Spark and Machine Learning. Previously he was a Senior Software Engineer at SecurityScorecard ("http://securityscorecard.com/) helping to build a reactive platform for monitoring real-time 3rd party vendor security risk in Java and Scala. Before that he was a Senior Field Engineer for Pivotal focusing on CloudFoundry, HAWQ and Big Data. He is an avid blogger and the Big Data Zone Leader for Dzone (https://dzone.com/users/297029/bunkertor.html). He runs the the very successful Future of Data Princeton meetup with over 1192 members at http://www.meetup.com/futureofdata-princeton/. He is currently a Senior Solutions Engineer at Cloudera in the Princeton New Jersey area. You can find all the source and material behind his talks at his Github and Community blog: https://github.com/tspannhw https://community.hortonworks.com/users/9304/tspann.html