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Should Digital Analysts
Become More Data Science-y?
Tim Wilson
#SPWK / @tgwilson
@tgwilson / #SPWK
Source: Flickr / KamiPhuc
October 10, 1993
@tgwilson / #SPWK
Mt. Katahdin
@tgwilson / #SPWK
Source: Google Maps
The end of a
5-month journey
@tgwilson / #SPWK
Source: Google Maps
…which was a
journey on foot.
@tgwilson / #SPWK
Source: Google Maps
@tgwilson / #SPWK
Which is like walking
from Barcelona to Moscow.
@tgwilson / #SPWK
Last year, I was on a
different journey.
@tgwilson / #SPWK
Source: Google Maps
Digital Analyst
Fall 2015
Intermediate R User
End of 2016
These journeys were
similar in many ways.
@tgwilson / #SPWK
Flickr / Ines Hegedus-Garcia
They were both challenging!
@tgwilson / #SPWK
They were both rewarding!
@tgwilson / #SPWK
They both turned out to have destinations
that weren’t as clear as I thought.
@tgwilson / #SPWK
Last year’s journey
@tgwilson / #SPWK
Source: Google Maps
Digital Analyst
Fall 2015
Intermediate R User
End of 2016
Last year’s journey
@tgwilson / #SPWK
Source: Google Maps
Digital Analyst
Fall 2015
Data Science-y Analyst
End of 2016
@tgwilson / #SPWK
But…
WHY?!
Because the Role of the
Digital Analyst Is Evolving
@tgwilson / #SPWK
The Spectrum of “Analytics”
Digital Analyst
Marketer
Basic Metrics Segmentation Data Science
@tgwilson / #SPWK
Data Science?!
Data Science
@tgwilson / #SPWK
Data Science
Wikipedia sayeth
employs techniques and theories drawn from many fields within the broad areas of:
@tgwilson / #SPWK
@tgwilson / #SPWK
@tgwilson / #SPWK
@tgwilson / #SPWK
is like boiling water.
PEAK1
Flickr / Revolution_Ferg
MSR Whisperlite
vs.
@tgwilson / #SPWK
@tgwilson / #SPWK
vs.
vs.
Programming Languages
Open Source (Free*)
Supported By Large Communities
Connectable to Digital Analytics
(and Other!) Data Sources
* TANSTAAFL
@tgwilson / #SPWK
Clingmans Dome
The highest point on the Appalachian Trail…
Flickr / David Fulmer
…and where I was during my undergraduate
commencement.
@tgwilson / #SPWK
Just as education arms us with
the power of knowledge…
...“programming” with data is powerful.
Flickr / David Fulmer
@tgwilson / #SPWK
Data Extraction
Flickr / Scott Swigart
@tgwilson / #SPWK
@tgwilson / #SPWK
One GA Account
Many Properties!
Many Views!
@tgwilson / #SPWK
22
lines of code
@tgwilson / #SPWK
22
lines of terribly written code
@tgwilson / #SPWK
17
lines of terribly okay written code
38Google Analytics views queried
IN
19
seconds
@tgwilson / #SPWK
@tgwilson / #SPWK
Pull all of the
views I can access
Filter to the one
account I care
about
Filter to only the
“production”
views
Pull the data for
each of those
views
Add that data to
my (filtered) list of
views
Export a .csv
Pretty up the
column names
@tgwilson / #SPWK
Yes!
Is this just an
alternative to Adobe’s
Data Warehouse?
…with more flexibility
…without the mystery
delivery time
Reusability
and
Extensibility
Flickr / Scott Swigart
@tgwilson / #SPWK
@tgwilson / #SPWK
Pull all of the
views I can access
Filter to the one
account I care
about
Filter to only the
“production”
views
Pull the data for
each of those
views
Add that data to
my (filtered) list of
views
Export a .csv
Pretty up the
column names
@tgwilson / #SPWK
Comparisons: (Top) 18 Web Sites
@tgwilson / #SPWK
Totals: Channel vs. Customer Segment
@tgwilson / #SPWK
Anomalies: Channels vs. Segments
@tgwilson / #SPWK
github.com/gilliganondata
@tgwilson / #SPWK
Data Science
@tgwilson / #SPWK
@tgwilson / #SPWK
“The clearest way into the universe is through a forest wilderness.”
- John Muir
“Numbers have an important story to tell. They rely on you to give them
a clear and convincing voice.”
- Stephen Few
0
20
40
60
80
100
120
140
160
180
200
1/3 1/10 1/17 1/24 1/31 2/7 2/14 2/21 2/28 3/6 3/13 3/20 3/27 4/3 4/10 4/17 4/24 5/1 5/8 5/15 5/22 5/29 6/5 6/12
@tgwilson / #SPWK
Where does R really stand out?
Flickr / Marina del Castell @tgwilson / #SPWK
VS.
Variety!
r-graph-gallery.com
@tgwilson / #SPWK
X X
Variety!
r-graph-gallery.com
@tgwilson / #SPWK
Variety!
r-graph-gallery.com
@tgwilson / #SPWK
How else does R stand out?
Flickr / Marina del Castell @tgwilson / #SPWK
My Perspective: Fall 2015
@tgwilson / #SPWK
Do the Analysis Communicate Results
@analyticshero
DATA VISUALIZATION
My Data Science-y Perspective
@tgwilson / #SPWK
Do the Analysis Communicate Results
@analyticshero
DATA VISUALIZATION
To be clear…
@tgwilson / #SPWK
…many tools offer
powerful data visualization.
Data scientists build visualizations that
are interactive and reactive.
@tgwilson / #SPWK
bit.ly/ga-explore
bit.ly/ga-explore
@tgwilson / #SPWK
bit.ly/ga-explore
@tgwilson / #SPWK
bit.ly/ga-explore
@tgwilson / #SPWK
bit.ly/ga-explore
@tgwilson / #SPWK
Data Science
@tgwilson / #SPWK
What is a p-value?
@tgwilson / #SPWK
“Informally, a p-value is the probability under a
specified statistical model that a statistical
summary of the data (for example, the sample
mean difference between two compared groups)
would be equal to or more extreme than its
observed value.”
– American Statistical Association
@tgwilson / #SPWK
@tgwilson / #SPWK
p-value:
Statistically significant pregnancy test.
This topic is…
Flickr / Howard Lake @tgwilson / #SPWK
As web analysts, how
often do we consider:
Correlations?
Regressions?
Confidence Levels?
Confidence Intervals?
Outlier Detection/Removal?
Type 1 vs. Type 2 Errors?
Bayesian vs. Frequentist
Approaches?
Flickr / Neil Piddock @tgwilson / #SPWK
@tgwilson / #SPWK
This is hard!
Flickr / Casey Fleser
Which Channels Have a Traffic Correlation?
@tgwilson / #SPWK
TODAY
The metric went down. Why?!
TODAY
Did the metric move enough for me to care?
Forecasts = The Future?
Actual Forecast
TODAY
(NOT FOR THIS, AT LEAST)
Let’s pretend “today” is in the past!
Actual Forecast
TODAY
PRETEND
“TODAY”
Let’s pretend ”today” is in the past!
Actual Forecast
PRETEND
“TODAY”
Actual Forecast
And let’s build a forecast from that point
PRETEND
“TODAY”
We know a forecast won’t be perfect.
Prediction Interval Actual Forecast
PRETEND
“TODAY”
Now we have meaningful context!
Prediction Interval Actual Forecast TODAY
What this can look like in the real world.
@tgwilson / #SPWK
And…drilling down and summarizing
@tgwilson / #SPWK
Mark Edmondson’s
Pre-/Post- Analysis Using a Bayesian Structural Time-Series Method
@tgwilson / #SPWKbit.ly/ga-effect
So, are YOU ready to put data science(-y-ness)
on your career roadmap?
STATISTICS
@tgwilson / #SPWK
Source: Flickr / Xavi
DATA
VISUALIZATION
COMPUTER
PROGRAMMING
The Measure Slack Team
@tgwilson / #SPWK
http://join.measure.chat
dartistics.com
@tgwilson / #SPWK
R and Statistics for the Digital Analyst
Columbus, Ohio, US – June 13-15, 2017
bit.ly/r-stats-training
Introduction to RDAY 1
The Basics
Taught by Tim Wilson and Mark Edmondson
Statistics for the
Digital Analyst
DAY 2
Putting R into
Practice
DAY 3
Real-World Digital Analytics Examples
Taught by Dr. Michael Levin, Otterbein University
Building Those Real-World Examples (and Advanced Topics)
Taught by Mark Edmondson and Tim Wilson
Flickr / Jeffrey Stylos
Slack/Twitter: @tgwilson
linkedin.com/in/tgwilson
tim@analyticsdemystified.com
Podcast: analyticshour.io
@tgwilson / #SPWK
2-D Tool: bit.ly/ga-explore
Website: dartistics.com
Slack: join.measure.chat
Training: bit.ly/r-stats-training

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Should Digital Analysts Become More Data Science-y?