Faircloth_DAT 530_Module 3_Short Paper_2023
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School
Southern New Hampshire University *
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Course
DAT530
Subject
Industrial Engineering
Date
Jan 9, 2024
Type
docx
Pages
8
Uploaded by Bearclaw512
Justin Faircloth
SNHU DAT-530
Module 3 Short Paper
Overview
Data visualizations serve as a powerful medium to convey complex information efficiently,
making intricate datasets accessible, comprehensible, and usable for informed decision-making.
By transforming raw data into visual formats, these tools facilitate a clearer understanding of the
underlying patterns, trends, and insights encapsulated within the data. Among the myriad of data
visualization tools available, SAS Visual Analytics and Tableau stand out as two easy-to-use
choices. Both tools offer a suite of features that support the creation of interactive, dynamic, and
engaging visual presentations, tailored to various audience needs. This paper introduces and
explores the distinctive capabilities and applications of SAS Visual Analytics and Tableau,
highlighting their respective strengths and limitations and comparing both effective and
ineffective visuals.
Visualization Presentation Comparison
Both SAS and Tableau have similar features to navigate data and make it easy for users.
However, this doesn’t mean that the two are identical in their features. A feature that truly stood
out to me between the platforms was how tabular data functioned. In the “Amur Leopards are
disappearing” visual and other tableau visuals instead of tabbing over to different visual the main
visual would change to represent different data. This means that the user has the ability to
manipulate the data without changing the page that they are on. In the “Water consumption by
date” visual from SAS you had to tab over to different tabs which reset the data on the page you
were previously on. There were some instances where the SAS visuals had same page
manipulations like “Net operating Income by Region” I did not see the functionality as often.
This leads me to believe that it may be more challenging to build on this platform. Many
universal features existed such as expanding or minimizing the visual manipulating the data, or
selecting specific sections. Most platforms have to have some features that exist as a baseline
feature set that people can navigate with minimal instruction or previous knowledge. Both the
“Manipulate Love for Books” and “Count of Highly Pathogenic Avian Influenza Outbreaks by
Country” visuals had easy-to-use manipulation by clicking around on various pieces of data. This
means that most audiences would be able to understand what to do with the visual
Which presentation features do you like and why?
One of my favorite features was how easy it was to do graph-to-graph data manipulation. In the
“RAROC vs Exposure by Lines of Business” you had a main visual that displayed the core data
for the topic but you are able to click through different data points and other smaller graphs near
the main visual would display different information. The overall variety of visuals available on
Tableau really highlighted the ability to build whatever the builder desired. Tableau also made it
very easy to embed the visual that is created into other places which did not seem like a
prominent feature on SAS. Both platforms made it very easy to drill down on data to find what
you need. In the “Drill down Boston Marathon Minutes” visual the viewer can select through the
categories and still see a shadow of the original data for context. In the SAS visuals you can
right-click on any visual to get more information as well this made it so that when I wanted to
look at more information on “Economic vs Regulatory Capital by Industry” I could select a
specific function using right-click and scroll.
Which presentation features do you dislike and why?
One feature that I didn’t enjoy using was the scroll function on the mouse. Specifically, in the
“Top Ten Water Consumers” visual it moved so erratically that you couldn’t account for what
you were scrolling past. If someone didn’t adjust their mouse scroll sensitivity the data flies
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around which doesn’t seem like what the builder intended. The other feature was the ability to
layer data functions which made it hard to navigate through the visual. In the “Tableau
Innovation History” visual I had to adjust my viewer settings to utilize certain drill-down
functions in the data.
Analysis of Effective Visualization Examples
Tableau City of Toronto Fire Incidents
Why is it effective?
This visual was one of my favorites because of how easy it was to use and understand. The
builder made sure to incorporate useful information without overcomplicating the drill-down
functions. The information is easy to select certain areas and still keep the useful data on the left.
Manipulating data on the left also helped to navigate the changes in the map giving different
areas to manipulate based on what you might be looking for.
SAS: Bank net operating income by geography and business unit
Why is it effective?
This visual from SAS caught my eye because of how simply the data was represented. It was
very straightforward when clicking through the information and didn’t present any data that was
difficult to comprehend. This means that a broader audience would be able to use the visual and
still get useful information. Instead of having to switch to different tabs, which other SAS visuals
rely on, this visual gives you several different options to manipulate the same page visual.
Analysis of Ineffective Visualization Examples
SAS: Water Consumption by Date Range
Why is it confusing:
I really struggled with this visual and understanding what I would use it for. As I zoomed in and
out on the graph the data didn’t give me further information. There was no unit of measurement
on the Y-axis and even when I selected the date range it didn’t give any more context. The hover
data gave further information to the plot points but not enough to be easily digested.
Tableau: Tableau Innovation History
Why is it confusing:
In this visual, the amount of information to click through made it hard to navigate. I enjoyed the
controls that were incorporated but it made it hard to know what to click on next. The table itself
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was information overload and if this visual were to be embedded somewhere with a zoomed-out
view you would get no information from the table due to its size and the font. The color choice
was a wide spectrum gold stands out a lot more than iron or water making it feel unbalanced.
Resources
2023 Boston Marathon
. (n.d.). Tableau Public.
https://public.tableau.com/app/profile/whitney6892/viz/bostonrunners/Dashboard1
Amur Leopards are Disappearing
. (n.d.). Tableau Public.
https://public.tableau.com/app/profile/asha4359/viz/AmurLeopardsareDisappearing/Dash
board1
Banking and Risk Insights - SAS® Visual Analytics
. (n.d.).
https://xaas-
17185005745.engage.sas.com/SASVisualAnalytics/?reportUri=%2Freports%2Freports
%2F3fc628c3-9d7b-4374-b829-
a229074286d8§ionIndex=0&printEnabled=false&shareEnabled=false&informationEnabl
ed=false&commentsEnabled=false&alertsEnabled=false&sso_guest=true&reportViewOn
ly=true&reportContextBar=false&sas-welcome=false
Emerging Disease Surveillance & Forecasting
. (n.d.). SAS.
https://www.sas.com/en_us/software/visual-analytics/demo/emerging-disease-
surveillance-forecasting/sas-visual-analytics-emerging-disease-surveillance-and-
forecasting-interactive-demo.html\
Re-Discovering the love for Books | #IronQuest #VizOfTheDay
. (n.d.). Tableau Public.
https://public.tableau.com/app/profile/varun.viz.vorkshop/viz/Re-
DiscoveringtheLoveforBooksIronQuest/viz
Retail Insights - SAS® Visual Analytics
. (n.d.). https://xaas-
17185005745.engage.sas.com/SASVisualAnalytics/?reportUri=%2Freports%2Freports
%2F994cd54c-a704-4915-be30-
87674e5351f5§ionIndex=0&printEnabled=false&shareEnabled=false&informationEnabl
ed=false&commentsEnabled=false&alertsEnabled=false&sso_guest=true&reportViewOn
ly=true&reportContextBar=false&sas-welcome=false
Tableau history
. (n.d.). Tableau Public.
https://public.tableau.com/app/profile/jmackinlay/viz/TableauHistory/History
Where On Earth People Aren’t
. (n.d.). Tableau Public.
https://public.tableau.com/app/profile/agata1619/viz/WhereOnEarthPeopleArent/Populati
onDensity2020
Water Consumption and Monitoring - SAS® Visual Analytics
. (n.d.). https://xaas-
17185005745.engage.sas.com/SASVisualAnalytics/?reportUri=%2Freports%2Freports
%2F1c3cc081-5706-4385-a2b2-
fbfc6ed83bf3§ionIndex=0&printEnabled=false&shareEnabled=false&informationEnabled=false
&commentsEnabled=false&alertsEnabled=false&sso_guest=true&reportViewOnly=true&report
ContextBar=false&sas-welcome=false