Getting Started With Data Science At Your Organization, Presented by Daniel Dunn

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Original content presented at the 2014 Nashville Analytics Summit

Data & Analytics

1
getting started with
DATA
SCIENCE
at your organization
© 2014 Daniel Dunn

RISK
reality check
Legacy Executives

3
Allies / Vision
lots of data
Permission
≠
Sponsorship
open-
+ minded
execs
=
Marketing!
formula: + lack of quants

4
creating
infra-structure
Long-Term:
•Mastered data
•Governed data
•Marts/BI tools
•Parallel
•Productionalization
Near-Term:
•Change management plan
•Data sandbox
•64-bit PC; mucho RAM
•SQL
•R / Rstudio
•GitHub
•Task Scheduler

5
> building
your team
T w i n
•business
intuition to
identify
problem
•identify
ideal data
set
•get data
•explore
dataset
•build model
•validate
model
•interpret
results
•create deck
•present
findings

3rd
largest economy
world’s
•Citation ≠ Validation
•Data Brief = King
•Reproducibility is a must for trust
•Readiness assessment
•Research pipeline
•No memorization
is the
Team
Principles

is the world’s
•Whatever internal advocates request
•Slam dunk that CFO will see
•Self-funding
Finding Projects
No
Win
Situation
No
Credit
High
Stakes
Sweet
Spot
Impact of Screwing Up
Business Leader Enthusiasm
FIFO
&
The Trojan
Horse

…for humility in analysis…
Everything simple is false. Everything
complex is unusable. -Paul Valery
…for setbacks…
It only ends once. Anything that happens
before that is just progress. -Lost
…for perspective…
You are the average of the five people
you spend the most time with. -Jim Rohn
some musings…

any questions?
Sources: http://xkcd.com/552/ ; duarte.com/book/slideology

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Detecting Credit Card Fraud: A Machine Learning Approach

Detecting Credit Card Fraud: A Machine Learning Approach

Detecting Credit Card Fraud: A Machine Learning Approach

Boston Institute of Analytics

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Getting Started With Data Science At Your Organization, Presented by Daniel Dunn

1. 1 getting started with DATA SCIENCE at your organization © 2014 Daniel Dunn

2. RISK reality check Legacy Executives

3. 3 Allies / Vision lots of data Permission ≠ Sponsorship open- + minded execs = Marketing! formula: + lack of quants

4. 4 creating infra-structure Long-Term: •Mastered data •Governed data •Marts/BI tools •Parallel •Productionalization Near-Term: •Change management plan •Data sandbox •64-bit PC; mucho RAM •SQL •R / Rstudio •GitHub •Task Scheduler

5. 5 > building your team T w i n •business intuition to identify problem •identify ideal data set •get data •explore dataset •build model •validate model •interpret results •create deck •present findings

6. 3rd largest economy world’s •Citation ≠ Validation •Data Brief = King •Reproducibility is a must for trust •Readiness assessment •Research pipeline •No memorization is the Team Principles

7. is the world’s •Whatever internal advocates request •Slam dunk that CFO will see •Self-funding Finding Projects No Win Situation No Credit High Stakes Sweet Spot Impact of Screwing Up Business Leader Enthusiasm FIFO & The Trojan Horse

8. …for humility in analysis… Everything simple is false. Everything complex is unusable. -Paul Valery …for setbacks… It only ends once. Anything that happens before that is just progress. -Lost …for perspective… You are the average of the five people you spend the most time with. -Jim Rohn some musings…

9. any questions? Sources: http://xkcd.com/552/ ; duarte.com/book/slideology