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August 03, 2016
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Intro: Play-by-Play: Data Hacks & Demos @ #HS16SJ

So, it’s been a month since Hadoop Summit San Jose, where over 5000 of the leading tech innovators in big data came together to share their inventions, wisdom and know-how. One of the sessions – a powerpoint free zone, was Data Hacks & Demos, a keynote session hosted by Joe Witt and starring an international team from the US, Germany, and UK: Jeremy Dyer, Kay Lerch, Simon Ball. The session was a 20 minute session that created a series of live interactive IoT and streaming analytics demos using Apache NiFi, Spark, Storm, Zeppelin, Azure, Raspberry Pi, Amazon EC2 and AWS IoT.

The demo  simulated how a brick and mortar retail store could identify which customers are walking in the door, speak to them, and then find out their preferences to be able to provide personalized offers in real time. The demo showcased how you can today:

  1. Correlate an image to an identifier, correlate it with other data points, and initiate a personalized, real time electronic conversation with a customer in store
  2. Algorithmicly prioritize specific images of interest to be sent to a larger pool of data and perform computer vision machine learning
  3. Use IoT technology to allow the customer to vote on their preferences
  4. Streaming analytics to create an accurate single buyer identity in real-time

In the next few blog posts, we will go through a play-by-play of how it really all went down, one demo at a time. First up, Demo #1

Data Hacks Demos Hortonworks Hadoop Summit Apache NiFi

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