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Summary of Insights Learned from the
Data Science Program Team Training
Fred Chiang (@fredchiang)
fredchiang@etusolution.com
The Lead of Etu and the DSP Committee Member
May 19th, 2014

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Agenda
1. What is DSP?
2. How did DSP become about?
3. What does DSP do?
4. What have we learned?

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What is DSP?

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Data Science Program (DSP)
DSP was initiated by Etu, Code for Tomorrow (CfT) and
supported by OKFN Taiwan and other various parties.
http://datasci.co

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DSP, is a case of enterprise run data-driven CSR
with NPO, from SYSTEX/Etu’s perspective
Etu, SYSTEX
Etu is a pioneer of Big Data providing Hadoop-based
solutions from Taiwan primarily focused on helping
customers discover, unlock, and utilize valuable information
embedded in extremely large data sets through simple
steps.
SYSTEX Group is an Asia-Pacific regional IT service provider
and the largest one in Taiwan.
Etu is an independent brand incubated by SYSTEX.
Code for Tomorrow
Code for Tomorrow (CfT) Foundation Initiative is a non-
profit organization that actively encourages governments,
private sectors, and civil society organizations to embrace
the power of the internet and people to better our
governance in the 21st century.

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codefortomorrow.org
How did it become about?
What does it do?
What have we learned?

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How did DSP become about?

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Harvard
Business
Review
October 2012
http://cromi.org/main/wp-content/uploads/2012/10/Davenport-2012-data-scientist.pdf
But where can we find these
sexy people and make them
work with us?

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No one person can be the perfect
data scientist, so we need teams
Source: Next-Gen Data Scientist, Dr. Rachel Schutt
Data Science Profiles

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Data Science Program Goal
Train 300talented data science team members
within 3years for Taiwan

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What does DSP do?

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DSP Working Group
Committee
CEO (CfT) / Principal Secretory (Etu)
Administration
Team
COO (Etu)
Curriculum Team
CCO (CfT)
Marketing Team
CMO (CfT)

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DSP Courses
(continuously developing)
1. Team Training
2. Data ETL and Analysis with Python
3. Data Journalism (coming soon)

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Who are interested?
Those who signed up for DSP Team
Training #1 #2. Totaling 168 counts
0 10 20 30 40 50 60 70 80
UI Designer
Art Designer
UX Designer
Other
Product/Service Planner
Story Teller
Programmer
Data Analyst
5
6
7
22
48
52
67
75
77%
23%
Male
Female
Analyst
Hygienist
Campaigner
Campaigner
Designer
Designer
Designer

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Self-tagging by Role
• Campaigner
• Analyst
• Hygienist
• Designer

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[DSP’s Motto #1]
“The point of statistics is not to do
myriad rigorous mathematical
calculations; the point is to gain insight
into meaningful social phenomena.”
~ Charles Wheelan
from the book ‘Naked Statistics: Stripping the Dread from the Data’

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[DSP’s Motto #2]

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• 2012.08 ~ 2013.09
• All (22) counties/cities of Taiwan
• About 470,000 records
Dataset 1:
Real Estate Transaction Data

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Dataset 2: PIXNET’s open data
The largest blog service
provider in Taiwan
Data opened:
1. Metadata of popular photo
2. Photo EXIF
3. Metadata of popular blog
4. Visitor logs of popular blog
*Article and photo can be retrieved by API
www.pixnet.net
http://developer.pixnet.pro/

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Data Fiesta: Team Project Showtime

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LOVE EASIER LIVING Infographic download: http://goo.gl/fKdXXi
Elder’s Happiness Index by a number of medical treatment resources, disease death,
education resources, recreation resources, and social participation of every district in Taipei

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What have we learned?

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Insights Learned from DSP Team
Training
1. Potential Data Science Members are everywhere.
But this does not matter without the ability to organize them and to
train them to reach their potential.
2. Access to individual specialized classes are
available.
But there are a lack of classes that combine all this knowledge and
integrate it to become a complete End-to-End course.
3. There is a great amount of Data out there,
especially within the Government.
But the Government lacks a powerful strategic plan of how to open
data for the betterment of society.
4. Insights are around us.
But these insights need to be turned into actions.

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More or Less
1. More Quality in Life, Less Cynic
2. More Real Strategy, Less Bluffing
3. Ｍore Data, Less Guessing
4. More Correlation, Less Summation
5. More Cross-over, Less Limitation
Do them right,
let Data Science help to make many things good

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Taipei, Taiwan
Add : 318, Rueiguang Rd., Taipei 114, Taiwan
Tel : +886-2-77201888
Fax : +886-2-87986069
www.etusolution.com