veyepar: Thin Client Data Science

Author(s):	Josh Levy
Location	A2
Date	mar Tue 19	Days Raw Files
Start	16:10	First Raw Start	15:57
Duration	00:50:00	Offset	0:12:47
End	17:00	Last Raw End	16:47
Chapters	00:00 0:24:46
Total cuts_time	30 min.

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The Data Science team at Vast builds data products informed by the behavior of
consumers making big purchases. Our big data is billions of user interactions
with millions of pieces of inventory. Recently we have adopted a data
processing, analysis, and visualization environment based on remote access to
IPython Notebook hosted by a powerful compute server.

Our Data Science environment is inspired by a Development environment proposed
by blogger Mark O'Connor. O'Connor advocates using an iPad as a thin client to
connect to a more powerful server in the cloud. The combination of tablet plus
server is better than a laptop for several reasons including:

The tablet is more portable and offers longer battery life than a laptop;

The server offers better performance (more and faster cores, more RAM, more
CACHE) than a laptop;

Laptops run loud and hot. The noise and heat of the server need not be close
the tablet or the ears and lap of the user;

The server is always running and the tablet can wake up and reconnect
instantly;

IPython Notebook is the keystone of our environment. It enables us to use the
tablet browser as a thin client to work with our favorite Python libraries
including matplotlb for visualization, scikit-learn for predictive modeling,
and pandas for processing and aggregation.

In this talk, I'll discuss configuring the Notebook server and the tablet
client. I'll also show examples and results of actual analyses performed in
this environment.

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