The pace of business disruption is accelerating, meaning today’s organizations need to become more data driven in order to compete and innovate. It’s no secret that big data initiatives are becoming more pervasive. But in order to process this vast amount of data, companies need data science and machine learning to find valuable insights. As they move to build smart applications powered by Big Data and new emerging technologies like IoT, new challenges are arising including how to move data science and machine learning into production. Oftentimes it is a laborious, manual-coding process that can take up weeks or months.

1. ©2016 Talend Inc
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©2016 Talend Inc
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©2016 Talend Inc
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©2016 Talend Inc
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5
Simple
Steps
for
Unleashing
the
Power
of
Big
Data
and
Machine
Learning

2. ©2016 Talend Inc
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Making
Sense
of
Volume
&
Complexity

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Challenges
In
Becoming
Fully
Data-­‐Driven
Lack
of
skillsets
Sample
of
data
instead
of
all
data
Long
3me
to
put
a
model
into
produc3on
(weeks/months)
Analy3cs
models
change
frequently
requiring
system
updates
Many
tasks
are
unproduc3ve
hand-­‐coding
1
2
3
4
5
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Automa3on
brings
speed
and
agility
No
longer
reserved
to
the
happy
few
Unleash
the
full
power
of
Big
Data
The
Importance
of
Data
Science
&
Machine
Learning
#TalendConnect

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How
to
Turn
Data
Science
Into
ProducHon?
Need
to
move
from
deploying
models
in
months
to
days/hours
DJ
Pa3l,
U.S.
Chief
Data
Scien3st
at
White
House
Office
The
IT
team
Iterate
&
Collaborate

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Bridging
the
Gap
Between
Data
Science
&
IT
Create/tune/train
predic3ons,
models,
scores
Opera3onalize
analy3cs
Con3nuous
delivery
Full
access
to
data
lake
for
modeling
Data
Scien3st
IT
Shorten
3me
for
IT
teams
to
deliver
#TalendConnect

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“Adapt or Die”

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Camera
Tracking
Systems
An
array
of
cameras
around
the
field
capture
the
players
and
ball
posi3ons
LIVE
Used
by
the
NBA
since
2011-­‐2012
Tennis
“hawk
eye”

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aggregate
the
speed
and
distance
run
of
each
player
IN
REAL
TIME
Our
goal:
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• The
camera
array
sends
a
feed
of
25
frames
per
second
• Each
frame
captures
the
x,y,z
coordinates
of
every
player
• A
live
feed
of
sport
data
is
actually
prefy
serious
Big
Data!
Challenges
#TalendConnect

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Demo
Architecture
Database
Inges3on
Process
Store
Visualize
Deliver
ALL designed in Talend

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Next
Step:
From
Analysis
to
PredicHon
Team
stats
Who
is
the
most
likely
to
score
next?
Which
team
is
going
to
win?
Individual
players
stats
Which
player
needs
a
rest?
Which
players
are
being
traded
(à
bring
in
historical
data)

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Asset
Performance
Management
eCommerce
opHmizaHon
Precision
Farming
Smart
Buildings
&
CiHes
Back
to
the
Enterprise
World

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5
Steps
to
Become
Fully
Data-­‐Driven
=
Insights
&
Value
GOAL
Access
to
Everything
1
Collaborate
2
ConHnuous
Delivery
3
Combine
Historical
+
New
4
Batch
+
Real-­‐Time
5

15. ©2016 Talend Inc
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©2016 Talend Inc
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©2016 Talend Inc
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©2016 Talend Inc
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Real-­‐Time
Big
Data
Sandbox
Download
your
Free
Sandbox
hfp://www.talend.com/products/real-­‐3me-­‐big-­‐data

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©2016 Talend Inc
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©2016 Talend Inc
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©2016 Talend Inc
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THANK
YOU!