Dataiku, Pitch at Data-Driven NYC, New York City, September 17th 2013

•

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Our pitch at Data-Driven NYC meetup on September 17th (http://datadrivennyc.com). Speaking about Data Scientists pains and how Dataiku Data Science Studio can help them to more than Data Cleaners and Data Leak Fixers !

Technologie Bildung

DATA

SCIENTIST

is

NOT

a
deﬁned
term
This
is
not…
a
Data
Scien9st

www.dataiku.com

-‐
@dataiku
-‐
@baAymarc

How
can
we

HELP

DATA
SCIENTISTS

to

FOCUS

on
the

REAL
PROBLEMS
?

Pain
points

•  Data
prepara9on
is
9me-‐consuming

•  Machine
learning
is
hard
to
understand

•  Insights
and
models
(almost)
never
reach

produc9on

Data
Science
Studio

•  A
democra9c
&
ready
to
use
Data
Science

Studio
to
start
innova9ng
with
data!

Ready
to
Use
Data

Science
PlaYorm

Common
playground
for

innova9on

Accessible
Sta9s9cs
&

Machine
Learning
for

everyone

Handle
real-‐life
data

Data
Science
Studio

Visual
and
Interac9ve
Data

Prepara9on

For
Data
Cleaners

Guided
Machine
Learning

For
non
Machine
Learning
Experts

Produc9on
ready

For
Data
Leak
Fixers

Visual
Data
Prepara9on

•  Interac9ve
UI
with
instant
feedback
and

sugges9ons

•  Reversibility
of
the
script,
data
integrity

•  Explora9on
of
data:
quick
analysis,
facets

•  Cleansing:
missing
values,
outliers,
parsing

•  Enrichment:
GeoIP,
Holidays,
joins

•  Produc9on-‐ready:
integra9on
within
a
ﬂow

Data
Science
Studio:

beneﬁts

•  Real-‐9me
and
interac9ve

–  Transforma9on
eﬀects
can
be
previsualized
in
real-‐9me

•  Transparent
and
traceable

–  Keep
the
full
history
of
your
data
transforma9on
logics
and

model
designs

•  Easy
access
to
machine
learning

–  Get
started
with
our
app
templates,
bootstrap
your
model

and
features
selec9ons,
then
go
further!

•  Scalable
and
Produc9on
Ready

–  Apply
your
recipes
on
your
cluster
on
terabytes
of
data

Dataiku
at
a
glance

•  Founded
in
2013
by
Data
and
Search
Engine
veterans

•  From
“data”
and
“haïku”

“data
can
be
big

solu;on
would
be
small

feel
the
hot
wind”

•  1
goal:
make
Data
Science
accessible
to
anyone!

Contact:
marc.baAy@dataiku.com
-‐
@baAymarc
-‐
github.com/dataiku

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One of the most popular buzz words nowadays in the technology world is “Machine Learning (ML).” Most economists and business experts foresee Machine Learning changing every aspect of our lives in the next 10 years through automating and optimizing processes. This is leading many organizations to seek experts who can implement Machine Learning into their businesses. The paper will be written for statistical programmers who want to explore Machine Learning career, add Machine Learning skills to their experiences or enter a Machine Learning fields. The paper will discuss about personal journey to become to a Machine Learning Engineer from a statistical programmer. The paper will share my personal experience on what motivated me to start Machine Learning career, how I started it, and what I have learned and done to be a Machine Learning Engineer. In addition, the paper will also discuss the future of Machine Learning in Pharmaceutical Industry, especially in Biometric department.

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