in the world of data analytics, there is a multitude of visualizat

in the world of data analytics, there is a multitude of
visualization products. This article (Using Tableau to Visualize)
discusses the methodology of teaching the use of these
visualization products. After reading the article you will find a
Gartner Magic Quadrant depicting the different manufacturers
of visualization products. In the leader quadrant, there are three
companies, Tableau, Qlik, and Microsoft Power BI. As the
Subject Matter Expert (SME), compare one major difference
between each of the products as it pertains to this article (i.e.:
online resources, online training, tutorials, etc.).
Read the scenario and assignment instructions in the You
Decide Overview. You have been asked by the hospital's board
of directors to prepare a risk management plan that will help to
develop a culture of safety throughout Little Falls Hospital. The
plan should address the National Patient Safety Goals and
strategies to be implemented throughout the organization.
Prepare a 750-word summary of the important components of
the plan, the resources that are required to be implemented, and
strategies to overcome some of the hospital's deficiencies. Your
primary text and journal and/or website research must be used
as a reference to support your analysis.
Scenario Summary
The Joint Commission has recently visited Little Falls Hospital
for its accreditation visit. Overall, the survey went well except
for the standards related to the 2010 National Patient Safety
Goals. The Joint Commission surveyors indicated that the
hospital has not devoted enough resources and staff into
achieving these goals.
As the new risk manager, you are aware of the following issues.
· There is no specific plan on how Little Falls Hospital will
address and achieve these goals. This has been handled on a
department-by-department basis.

· Recently, there has been a significant plaintiff settlement paid
by the hospital's insurance carrier, which involved a patient
death related to the incorrect medication being administered.
· The costs of the hospital's professional liability insurance
continue to escalate, and the policy is due to expire in 6 months.
Little Falls Hospital has had the same health professional
liability insurance policy for 10 years.
· The hospital is facing financial constraints and does not have a
significant amount of cash on hand to invest in new
technologies.
Your Assignment
You have been asked by the hospital's board of director's to
prepare a risk management plan that will help to develop a
culture of safety throughout Little Falls Hospital. The plan
should address the National Patient Safety Goals and strategies
to be implemented throughout the organization. Prepare a 750-
word summary of the important components of the plan, the
resources that are required to implement, and strategies to
overcome some of the hospital's deficiencies. Your primary text
and journal and website research must be used as a reference to
support your analysis.
Key Players
Mr. Howard—Joint Commission Surveyor
Overall, I believe that Little Falls Hospital provides good
quality care to its patients. The hospital scored very high in
many aspects of the survey, but it did not seem focused on the
Joint Commission National Patient Safety standards. The
knowledge and understanding of these goals was inconsistent
among staff; however, some of the departments had little
awareness on how these goals impact the operations.
Communication is definitely a problem.
Barbara Gillium—Director of Radiology
I have attended several conferences in the last couple of years
and these goals have always been an important topic of
discussion. The radiology department has always prided itself in

quality care, and we do everything we can to make sure our
patient care is not only the highest quality but also the safest
possible.
Max Dillon—Hospital Pharmacist
The pharmacy department has always been one of the best
departments in the hospital. I keep asking for the money to
invest in technology but I always get denied. I think that our
current systems are more effective than the latest technology.
You invest all that money, but it is the same humans who are
providing care and dispensing medicines. I think sometimes that
computerized systems give staff a false sense of security when
they should be doing their jobs accurately anyway.
Grading Rubric
Category
Points
Description
Understanding
20
Demonstrate a strong grasp of the problem at hand.
Demonstrate understanding of how the course concepts apply to
the problem.
Analysis
20
Apply original thought to solving the business problem. Apply
concepts from the course material correctly toward solving the
business problem.
Execution
10
Write your answer clearly and succinctly using strong
organization and proper grammar. Use citations correctly.
Total
50
A quality paper will meet or exceed all of the above
requirements.

Contents lists available at ScienceDirect
Journal of Accounting Education
journal homepage: www.elsevier.com/locate/jaccedu
Using Tableau to visualize data and drive decision-making☆
Jamie Hoelschera,⁎ , Amanda Mortimerb
a School of Business, Southern Illinois University Edwardsville,
Box 1104, Edwardsville, IL 62026, United States
b PricewaterhouseCoopers, United States
A R T I C L E I N F O
Keywords:
Data analytics
Data visualization software
AACSB Accounting Standard A7
Business decision-making
Accounting educational resource
A B S T R A C T
This case emphasizes the importance of data analysis through
the usage of data visualization
software to help you gain an understanding of data and how it
can be transformed into in-
formation that can enhance the decision-making process. In the
data visualization software,
Tableau, you will be asked to connect to an Access data file to
analyze six months of sales

transaction data of a small start-up ice cream manufacturer.
Consistent with AACSB Accounting
Standard A7, the case focuses on familiarization with data
visualization software to “convey data,
results, and insights” (AACSB, 2013) and apply higher-order
thinking. Upon familiarization with
the data and data visualization software, you will be required to
perform an exploratory analysis
to identify key trends in the data to prepare and report that
information to enhance the business
decision-making process. This case is intended to be utilized in
an undergraduate accounting
information systems course; an introductory managerial course;
or a course focusing on data
analytics as a basic introduction to data visualization software.
1. Case
Ivana’s Ice Cream just finished its first six months of
manufacturing and selling ice cream. The company has two
main product
lines, ice cream cups and ice cream bars, both of which are
available in vanilla or chocolate flavors. Ivana Cone, the sole
owner of
Ivana’s Ice Cream, has carefully recorded basic accounting
data, including sales transaction data over the company’s first
two quarters
of operations using Microsoft Access. Unfortunately, Ivana
lacks formal business and accounting training. You have been
hired as a
consultant to utilize Tableau data visualization software to
analyze the company’s data from the first two quarters of
operations and
to provide a detailed breakdown of sales, product mix, and
gross profit by product line and geographic region. In addition,
Ivana

would like to expand the business in future years and you have
been asked to provide insights and recommendations. First, you
will
need to understand the business and operations.
The first step in any data analytics project is to thoroughly
understand the data and its current format. To learn more about
data
analytics in the field of accounting and the benefits and uses of
data visualization software see Appendices A and B,
respectively.
When creating visualizations, it is important to consider which
type of graph or chart best fits the data. Although there are
numerous
types of visualizations (graphs and charts) from which to
choose, some of the most common include bar charts, line
graphs, pie
charts, and maps. The data can help you determine which
visualizations would help convey the information most
effectively. For
example, bar charts are useful when data are separated into
different categories, while line graphs are useful to show
changes in data
over time. Pie charts display categories as a portion of a total,
and maps represent data geographically and should only be used
if the
https://doi.org/10.1016/j.jaccedu.2018.05.002
Received 11 October 2017; Received in revised form 22 May
2018; Accepted 23 May 2018
☆ This manuscript is one in a series of manuscripts that will
appear in the virtual Special Issue 2017 Teaching, Learning and
Curriculum Midyear Colloquium. In the
virtual SI, this will appear under the heading “Educational
Case”.

⁎ Corresponding author.
E-mail addresses: [email protected] (J. Hoelscher),
[email protected] (A. Mortimer).
Journal of Accounting Education 44 (2018) 49–59
Available online 14 July 2018
0748-5751/ © 2018 Elsevier Ltd. All rights reserved.
T
http://www.sciencedirect.com/science/journal/07485751
https://www.elsevier.com/locate/jaccedu
mailto:[email protected]
http://crossmark.crossref.org/dialog/?doi=10.1016/j.jaccedu.201
8.05.002&domain=pdf
data contains location information. Furthermore, Tableau has
the ability to suggest a visualization based on the types of fields
that
you select; this can be a very convenient feature when learning
to create visualizations.
Before you examine the Access database Ivana has given you,
she would like to tell you a little about the current state of her
startup company and the three tables she created to store the
company data. She created individual tables for customers,
orders, and
company products. Currently, Ivana’s Ice Cream only sell s
boxes of ice cream cups and ice cream bars, and each come in
either vanilla

or chocolate. Below is the unit cost and sales price for each
item Ivana’s Ice Cream currently sells (see Exhibit 1):
Ivana’s Ice Cream currently has twenty-two customers. In
general, these customers are smaller retailers, including
convenience
stores and local supermarkets. Currently, Ivana’s Ice Cream
only sells to retailers in the Midwest states of Missouri and
Illinois. Below
is a list of all of the customers with which Ivana’s Ice Cream
has done business with since its inception (see Exhibit 2).
Ivana’s Ice Cream currently has four sales representatives. For
simplicity, Ivana has assigned Levi Adams to western Missouri;
Gabby Bennet to eastern Missouri; Russell Bishop to western
Illinois; and Carly Marshall to eastern Illinois (see Exhibit 3).
Your instructor will provide you with the Microsoft Access data
files to complete the requirements of this case.1 Your instructor
may also assign you specific training videos from the Tableau
website (www.tableau.com) to familiarize you with the data
visua-
lization software, as well as information related to downloading
your free student copy of Tableau. Watching the first few
training
videos at http://tableau.com.learn/training will help better
prepare you for the requirements of this case study.
Before beginning the following case requirements, download the
Microsoft Access file provided to you by your instructor and
save
it to your desktop or a personal flash drive. Open the Access
file and examine each of the tables, as well the data types of
each of the
fields, and any primary keys identified. You will connect to
Ivana’s data and analyze the data using Tableau, as described

below.
2. Requirements
Being new to Tableau, a colleague has provided the following
tips to help you begin your analysis of Ivana’s Ice Cream using
Tableau:
1. Ensure you have downloaded the latest version of Tableau.
Visit https://www.tableau.com/academic/students to obtain a
free
one-year Tableau license for students.
2. Ensure you have saved the Ivana’s Ice Cream Access file
provided by your instructor to your desktop or personal flash
drive.
3. Double click on the Tableau Desktop icon to open Tableau.
4. Under “Connect To a File,” select “Access.”
5. Browse for the Ivana’s Ice Cream file and select “Open.”2
6. Drag each table to the open pane.3
7. Select Sheet 1 to go to your first worksheet.
Before you conduct your own exploratory analysis, Ivana Cone
would like to understand some basic information related to her
enterprise. Specifically, she would like you to answer the
following questions to be included and returned in a formal
memo to her
(below, your colleague has provided step-by-step instructions to
enable you to successfully address each of Ivana’s questions in
Tableau):
1. What is the total quantity sold of chocolate ice cream cups?
• From the Dimensions pane, drag Flavor and Product to the

Rows pane (by holding the Ctrl button down after you select
Flavor
and before you select the Product dimension, you can drag and
drop both dimensions at the same time).
• From the Measures pane, drag Quantity to the Columns pane.
• Hover your pointer over the bar for chocolate ice cream cups
and record the quantity of chocolate ice cream cups sold during
the period.
• Click on the top of the graph where it is currently titled “Sheet
1.” Rename the graph “Quantity Sold by Product.”
ProductID Product Flavor Unit cost Sales price
1 Ice Cream Cup Chocolate $2.55 $4.00
2 Ice Cream Cup Vanilla $2.50 $4.00
3 Ice Cream Bar Chocolate $3.00 $5.00
4 Ice Cream Bar Vanilla $2.85 $5.00
Exhibit 1. Product table.
1 Please e-mail [email protected] to request the Microsoft
Access file for this case.
2 If you are unable to connect to your Access database in
Tableau, please go to https://www.tableau.com/support/drivers
and search for Microsoft Access to
download the driver necessary to connect to your Access file.
3 Drag the tables over in order so they may properly join.
Notice how the Customer table and Orders table are inner joined
on the Customer ID field, and the Orders
table and Products table are inner joined on the ProductID field.
J. Hoelscher, A. Mortimer Journal of Accounting Education 44
(2018) 49–59

50
http://www.tableau.com
http://tableau.com.learn/traini ng
https://www.tableau.com/academic/students
https://www.tableau.com/support/drivers
ID Customer name Address City State ZIP Region
C00101 Grandma’s Grocery 6524
Oaktree Dr.
Springfield MO 65082 W MO
C00102 K & K Quick Mart 4817 Main
St.
Joliet IL 60403 E IL
C00103 Fresh Foods 436
Whitedge
Blvd.
Peoria IL 61602 W IL
C00104 Sandy’s Superstore 1525
Parkview
Dr.
Rolla MO 64801 W MO
C00105 Midwest Market 6401 Manor
Circle

Galesburg IL 61401 W MO
C00106 Food N Stuff 9452
Bridgeport
Ln.
Joplin MO 64801 W MO
C00107 Capital City
Grocery
684 First
Street
Jefferson
City
MO 65101 E MO
C00108 John’s Supermarket 2174
Washington
Ave.
Warrensburg MO 64093 W MO
C00109 Mini Mart 3355
President
Ct.
Aurora IL 60503 E IL
C00110 MJC Deli 42
Greenview
Blvd.

Champaign IL 61820 E IL
C00111 Paul’s General
Store
5551
Market St.
Mount
Vernon
IL 62864 E IL
C00112 Family Pantry 985 Wilson
Dr.
Jacksonville IL 62650 W IL
C00113 Garry’s Mini Mart 7931 North
1st St.
Sedalia MO 65301 W MO
C00114 Market Deli 1 Harvard
Dr.
Belleville IL 62223 W IL
C00115 B&B Convenience
Store
160 Grand
Ave.
Columbia MO 65202 E MO

C00116 Express Grocery 252
Washington
St.
Bloomington IL 61704 E IL
C00117 Bargain Mart 9956 Maple
St.
De Kalb IL 60115 E IL
C00118 Quality Foods 112 Henley
Ln
Jefferson
City
MO 65109 E MO
C00119 Local’s Cupboard 1411 West
Park Dr.
Fulton MO 65251 E MO
C00120 Salem Wholesale 25 Willow
Dr.
Salem MO 65560 E MO
C00121 Gas ‘N Go 9852 Peach
St.
Nashville IL 62263 W IL
C00122 Dollar Deals 333 Main

St.
Poplar Bluff MO 63901 E MO
Exhibit 2. Customer table.
(2018) 49–59
51
• At the bottom of the toolbar where it also shows “Sheet 1,”
right click on the tab and select “Rename Sheet.” Rename the
sheet
“Quantity Sold by Product.” 4,5
2. On what date were the most products sold (quantity-wise)?
• From the Measures pane, drag Quantity to the Rows pane.
• From the Dimensions pane, drag Order Date to the Columns
pane.
• The order date is being aggregated at the yearly level. To
disaggregate and get a daily sum, click on the + in the YEAR
(Order
Date) to expand to a quarterly measure. Continue to expand
until you get a daily measure.
• View the line graph to identify the date with the largest
quantity of products sold.
• Name the graph “Quantity Sold by Date.”
• Rename the sheet “Quantity Sold by Date.”
3. What is the total dollar amount of sales for vanilla ice cream
bars?6

• In your new sheet, create a new calculated field, select
“Analysis” from the tool bar, and then select “Create Calculated
Field.”7
• Name the newly calculated field “Sales Total.”
o The sales total should be calculated by multiplying Quantity
by Sales Price. [Sales Price] ∗ [Quantity]
o Notice you are told “the calculation is valid.” Select “OK.”
• From the Dimensions pane, drag Flavor and Product to the
Rows pane.
• From the Measures pane, drag your newly created field, Sales
Total, to the Columns pane.
• Select the bar for vanilla ice cream bars to examine the sales
total for this product line.
• Name the graph “Sales by Product.”
• Rename the sheet “Sales by Product.”
4. Which item has the highest sales for the period? What is the
amount of sales for that item?
• This answer can be determined by examining the “Sales by
Product” visualization.
• Document which item has the highest dollar sales for the
period and what the amount of sales were for that item.
5. Which flavor has the lowest sales for the period? What is the
amount of sales for that flavor?
• This answer can also be determined by examining the “Sales
by Product” visualization.
• As this question only asks about flavors, and not a specific
product, remove Product from the Rows pane by dragging and
dropping Product back into the Dimensions pane.8

• To make the visualizations accurately color coded, drag Flavor
from the Dimension pane and drop it on Color in the Marks
pane.
o Click on Color and then select “Edit Colors.”
o Make chocolate brown and vanilla an off-white color.
o Select “OK.”
• Identify which flavor has the lowest sales for the period and
the amount of sales for that flavor.
• Rename the visualization and the sheet “Sales by Flavor.”
6. How much of the chocolate flavor sales are attributed to sales
of ice cream bars?
Flavor” sheet.
• From the Dimensions tab, select “Product” and drag and drop
it on Color in the Marks pane.
• You will now see how much of each flavor’s sales are
attributable to which product.
• Hover over the chocolate bar to determine how much of the
chocolate flavor sales are attributed to the sale of ice cream
bars.
7. Which graph type would be recommended to show sales by
day of the week? Which day of the week has the highest dollar
amount of sales? What is the total dollar value of sales on that
day of the week?
• In a new sheet, select Sales Total from the Measures pane,
Ctrl and Day of the Week from the Dimensions Pane.
• From the Show Me toolbar, see the variety of visualizations
that can be used, but note which chart is recommended
(bordered)
to visualize your specific data.

Sales representative Region
Levi Adams Western Missouri
Gabby Bennet Eastern Missouri
Russell Bishop Western Illinois
Carly Marshall Eastern Illinois
Exhibit 3. Sales representative table.
4 Click on the tab next to your newly created sheet name (with
the + sign) to create a new sheet and begin work to answ er the
next question.
5 Changing the sheet name first will automatically update the
graph title to the same name.
6 You currently only have measures based on quantity, unit cost
per item, and sales price per item. To capture the total sales
price, a new measure must be created.
7 You can also right click in the Measures pane, select
“Create,” and then select “Calculated Field.”
8 Alternatively, to keep the existing visualization intact, you
can copy the existing sheet and begin working from the copy.
Simply right click on the sheet tab of the
sheet you would like to copy and select “Copy Sheet.” Then, on
the tab for a new sheet, right click again and select “Paste
Sheet.”
(2018) 49–59
52
• Double click on the suggested visualization type.9
• Verify the Sales Total measure was brought to the Columns
pane and the Day of Week dimension was brought to the Rows

pane
to illustrate your visualization.
• Examine which day of the week has the highest dollar amount
of sales.
• Rename the graph and sheet “Sales by Day.”
8. Which sales representative has the lowest dollar amount of
sales on Mondays? What is the total dollar amount of that sales
representative on Mondays?
Day” sheet.
• From the Dimensions pane, drag Sales Representative to the
Rows pane.
• Examine which sales representative has the lowest dollar
amount of sales on Mondays.
• Rename the graph and sheet “Sales Rep Sales by Day.”
9. What are the total sales for the period?
• In a new sheet, drag Sales Total from the Measures tab to the
Columns pane.10
• Examine total sales for the period.
• Rename the graph and sheet “Total Sales.”
10. Which sales representative has the highest dollar amount of
sales, and what was the dollar amount?
• In the same sheet, change the chart type from Automatic to Pie
in the Marks card.
• Drag Sales Total from the Rows pane to Angle in the Marks
card.
• Drag Sales Representative from the Dimensions pane to Color
in the Marks card.
• For reference, in the Marks card, click on Label. Select “Show

Label” and under “Marks to Label,” select “All” to show the
total
sales revenue for each sales representative.
• Examine which sales representative has the highest dollar
amount of sales.
• Rename the graph and sheet “Sales by Rep.”
11. What is the total gross profit for Ivana’s Ice Cream?
• In a new sheet, create a new calculated field.
o COGS = [Cost] ∗ [Quantity]
o Select “OK”
• Create another calculated field.
o GP = [Sales Total] − [COGS]
• Drag your newly created measure, GP, to the Columns pane.
• Examine the total gross profit for Ivana’s Ice Cream.
12. What is the average gross profit among all sales
representatives?
• From the Dimensions pane, drag and drop Sales
Representative into the Rows pane.11
• To determine the average gross profit per sales representative,
select the Analytics tab and drag and drop the average line into
the Graphic pane.
• Examine the average gross profit per sales representative.
• Rename the graph and sheet “Gross Profit.”
13. Which geographic region has the least customers?
• If Tableau does not already recognize the ZIP code field as a
geographical field (shown by the globe icon to the left of the

dimension), you will have to assign a geographic role.
• Click on the down arrow next to ZIP code in the Dimensions
pane.
• Hover your mouse over Geographic Role, and then select “ZIP
Code/Postal Code.”
• In a new sheet, hold down Ctrl while selecting Latitude
(generated) and Longitude (generated) from the Measures pane
and ZIP
Code from the Dimensions pane.
• Select the recommended graph from the Show Me toolbar.
• Drag Region from the Dimensions pane and drop it on Color
in the Marks card.
• Rename the graph “Customers by Region.”
• Examine the customers by geographic region.
14. Which ZIP code generates the highest gross profit?
• In the same sheet, drag Gross Profit from the Measures pane to
Size on the Marks card.
• Identify the ZIP code which has the largest gross profit.
9 Depending upon the type of data you are trying to visualize
(i.e., how many dimensions and measures you have), it is
important to know which type of chart is
preferred to display your data. For example, bar charts are very
intuitive and enable the user to quickly examine highs and lows
in the data when you have categorical
variables, whereas line charts enable a user to see changes or
trends over time. Pie charts are helpful when you would like the
user to examine relative proportions.
Based on the dimensions and measures you are wanting to
capture in a given visualization, Tableau recommends the type
of visualization that would best display your

given data. See the Tableau Whitepaper entitled, “Which chart
or graph is right for you?” for further information regarding
how to select the appropriate visualization
for your data (Tableau, 2017a).
10 Note that for one measure, Tableau recommends a horizontal
bar graph.
11 Note that for one measure and one dimension, Tableau
recommends a horizontal bar graph. To have a vertical bar
graph, you can simply move the dimension
(Sales Representative) to the Columns pane and the measure
(GP) to the Rows pane.
(2018) 49–59
53
Compile each of your answers on a memo to Ivana in numerical
form.
2.1. Additional case requirements
Before you updated Ivana with the results of your previous
analysis, Ivana emails you with a few additional questions.
Unfortunately, your colleague who is a Tableau expert is on
vacation and unable to provide you with guidance for the
follow-up
analysis. Address each of the following additional questions
posed by Ivana in your memo:
Ivana: “I want to make sure we treat our biggest customers the
best, as it is vital we do not lose their business. I might consider
offering discounts to our best customers in the future. Who is

our biggest customer, and what is the total revenue from that
customer so far? Also, what is the total gross profit from that
customer?”
“I want to make sure my best sales representatives are
rewarded. Since Ivana’s Ice Cream opened, I have been paying
my sales
representatives a flat rate, but I need to start paying them based
on their production levels. Who sold the most units in
September
2016? How many units did that sales representative sell?”
“In your analysis, did you notice any trends in the data or
general areas of concern that warrant my attention?”
3. Teaching notes
3.1. Learning objectives
The case uses sales transaction data to engage students i n the
utilization of data analytics to drive decision-making. The case
has
several objectives consistent with AACSB Accounting Standard
A7 (AACSB, 2013) to stimulate student learning, including:
1. Applying data analytics to understand company data.12
2. Utilizing data visualization software to present results needed
to make key business decisions.
3. Applying data analytics to observe key data trends.13
4. Applying data analytics to enhance the business decision-
making process.
5. Enhancing verbal and written communication skills to
effectively disseminate data trends and business
recommendations.

Paralleling these objectives, the case also aligns with the
AICPA Core Competency Framework (AICPA, 2017) as shown
in Table 1.
3.2. Implementation guidance
The case was created to provide an introduction to data
visualization software and the basics of data analytics.
Apostolou,
Dorminey, Hassell, and Rebele (2014) emphasize the need for
instructional educational cases that address emerging
technologies and
their usage in the accounting profession. While few accounting
educational case studies have been developed to focus on data
analytics (Igou & Coe 2016; Janvrin, Raschke, & Dilla, 2014;
Kokina, Pachamanova, & Corbett 2017), many focus more on
the
accounting task and less specifically on the data visualization
software functionality and user interface. More specifically,
many cases
(Igou & Coe, 2016; Janvrin et al., 2014; Kokina et al., 2017) do
not focus on understanding the underlying data set,
understanding
dimensions and measures or understanding when different types
of graphs are suitable for use. For example, Brazelton (2000)
finds
Bloom’s revised taxonomy of learning to be directly applicable
to accounting students, but lower-level skill sets such as
remembering,
Table 1
Alignment with AICPA Accounting and Professional
Competencies.
Accounting competencies:

Technology and tools Students leverage data visualization
software to better understand transaction data from a relational
database, create new calculated
fields, aggregate fields, data mine, observe key trends and
document and present results
Professional competencies:
Decision making Students perform various data analytic
techniques to examine and visualize data trends to instill the
link between data, knowledge and
insight to enhance the decision making process and make
optimal recommendations
Communication Whether done individually or in small groups,
students fine-tune their written (and verbal skills if done in a
group or presented to the
class) communication skills to effectively deliver and convey
data insights in a professional memo
Collaboration If done in small groups, students work
productively with diverse peers to achieve a common goal
12 Results of case efficacy related to students’ ability to apply
data analytics to understand company data and utilize data
visualization software to present results is
shown in Panel A of Table 2. Additional results of indirect
evidence related to case efficacy related to case objectives is
shown in Table 3.
13 Results of case efficacy related to students’ ability to apply
data analytics to observe key data trends and enhance verbal
and written communication skills to
effectively disseminate data trends and business
recommendations to enhance the decision-making process are
shown in Panel B of Table 2. Additional results of
indirect evidence related to case efficacy related to case

objectives is shown in Table 3.
(2018) 49–59
54
understanding, and applying must first be acquired before
higher-level skills such as analyzing, evaluating, and creating
can be
mastered. Oftentimes, students in undergraduate accounting
information systems courses have not yet completed that course
se-
quence and are in differing levels of the accounting curriculum.
This case study provides a basic introduction of data
visualization
software and encourages students to gain a thorough
understanding of the data in order to determine which type of
visualization
would be most useful to display the underlying data to the end
user, and thus work sequentially through Bloom’s taxonomy.14
The case can be used as a standalone case in or out of the
classroom. Unlike many other data analytic cases (Igou & Coe
2016;
Janvrin et al., 2014,15 Kokina et al., 2017) that require
anywhere from two hours up to four 75-min class periods, this
case can be
structured to be completed within the confines of a normal 75-
min class setting (or as a standalone homework assignment).
For our initial pilot study, the case was assigned to an
undergraduate accounting information systems class upon
learning basic

database design skills within both Microsoft Excel and Access.
The students had no previous exposure to data visualization
software
or Tableau.16 The case was assigned as an individual, take-
home assignment. Students were required to submit their
answers to each
question, as well as the follow-up and exploratory analysis in a
memorandum (sample memorandum shown in the case
solutions).
Students were not required to present their findings to the class.
Upon completion of this introductory case study, students
completed
other, more advanced data analytic and data visualization cases
with more ease and success than previous sections of the course
where this case had not been administered.
In later semesters, the case was administered in class, in small
groups of two to three students. Students were instructed to read
the case in its entirety, download Tableau to a PC (if not in a
lab setting), and download the Access data files from the course
website
prior to class. Students were given the entire class period to
work through the case. Most groups were able to complete the
guided
questions and exploratory portions of the case, but many groups
did have to finalize the formal memo outside of class as
homework.
If the instructor is able to devote more class time to the case,
the instructor may require students to prepare a formal
presentation
to the class to present their visualizations and memo. This will
also facilitate class discussion, as it is unlikely all students will
identify
every key data trend that could be discovered and disseminated
to Ivana. Conversely, if in-class time does not allow for formal

presentations, instructors may wish for their students to prepare
a video presentation of key findings, visualizations, and re-
commendations.
3.2.1. Alternative implementation guidance
The case study could be incorporated into an introductory data
analytics course or a higher-level auditing or internal auditing
course. The emphasis of the case would then shift from the
guided demo and related questions to the follow-up, self-guided
ex-
ploratory questions. Students could be asked to provide detailed
visualizations (all visualizations provided below in the case
solu-
tions), including a dashboard or story detailing the key data
trends they discovered and how Ivana should use the
information to
drive business decisions going forward. The case also lends
itself well to an in-class small group exercise.
The case could also be tailored for an introductory cost or
managerial course. For brevity, the memo and additional
requirements
could be omitted to allow students to focus on the accounting
related issues, such as: gross profit, cost of goods sold, pr ofit
by product
line, profit by sales representative, profit by geographic region,
and other calculated fields.
3.3. Evidence of efficacy
The case was tested at a residential campus of a public
university in the Midwest, and the instructor was one of the
authors. This
case was tested for efficacy from three sections of an
undergraduate accounting information systems course over the

spring 2017 and
fall 2017 semesters. The case was also tested for efficacy in a
graduate level internal auditing course.17
While the majority of students were not previously familiar with
data visualization software in general, Table 2 provides a
breakdown of case outcomes. Panel A reports the assessment
results of the students’ ability to learn data visualization
software and
apply data analytic techniques.18 As the first half of the case
was guided, with step-by-step instructions, only 5.94% of
students did
not meet expectations. Panel B reports assessment results of
students’ ability to apply the data analytic techniques they were
taught to
answer questions pertaining to business operations and to then
apply analytic techniques in an unstructured context.19 Lastly,
stu-
dents must report and disseminate their findings in a
professional memo to enable users of the information to
enhance their business
decision making. All but 8.64% of students at least met
expectations. In addition, almost 30% of students exceeded
expectations and
were able to prepare a professional memo in good form, while
also addressing Ivana’s specific questions and also identifying
many
key data trends that Ivana should consider in future business
decisions.
To further assess case efficacy, a survey was administered upon
completion of all case requirements, but prior to receiving
graded
14 Students are encouraged to consult Tableau’s white paper
entitled, “Which chart or graph is right for you?’ to understand

the choice of a visualization should be
carefully considered and is dependent upon not only the type of
data to be displayed but also the business decisions the user
needs to make.
15 The appendix to “Vistabeans coffee shop data analytics
teaching case” (Igou & Coe, 2016) does provide limited general
guidance on using Tableau, but the
majority of the case is more open-ended and exploratory in
nature. In addition, the appendix demo does not illustrate the
full functionality or plethora of visualization
types offered in Tableau, nor is either one the focal point of the
case study. “Vistabeans” would be an encouraged follow -up
case after the completions of this case.
16 In order to gain a more thorough understanding of the
company and the transaction data, students can be instructed to
examine the Microsoft Access relational
database prior to connecting to the data in Tableau and
beginning the actual data analysis.
17 The graduate internal auditing course has a significant
emphasis on data analytics and is an elective in the graduate
school’s Specialization in Business Analytics
program.
18 Panel A assesses students’ achievement of learning
objectives 1 and 2.
19 Panel B assesses student’s achievement of learning
objectives 3, 4, and 5.
(2018) 49–59
55

feedback on the case. Student questionnaires and surveys are
commonly used metrics to both assess case efficacy and obtain
student
feedback (Braun, 2013; Churyk & Stenka, 2014). Students
designated the extent to which they agreed or disagreed with the
following
statements by using a Likert scale from 1 to 7, in which “1”
denoted they “strongly disagreed” and “7” denoted they
“strongly agreed”
to each debriefing question.20
Table 3 provides the basic descriptive statistics of student
survey responses for each of the questions above. The
debriefing survey
results suggest that students used a variety of skills to solve the
case and found the case to be both engaging and interesting.
Consistent with the case learning objectives, the debriefing
survey results also indicate that as a result of completing the
case,
students have a better understanding of how to analyze data,
specifically in Tableau. In addition, as a result of completing
the case,
students report being more comfortable creating data
visualizations in Tableau than in Excel. Lastly, consistent with
overall case,
AACSB Accounting Standard A7, and accounting information
system course objectives in general, upon completion of the
case study,
students have a better understanding of the big picture (i.e.,
how data analytics and data visualizations can help drive better
business
decision making).
The debriefing survey also contained an open-ended qualitative
section where student feedback was solicited to provide other

comments and suggestions regarding the case. Student responses
to this question further indicate the ease of use and benefit of
this
case, as denoted below.
Table 2
Direct assessment of learning objectives and case outcomes.
Panel A: Assessment of student's ability to learn data
visualization software
n = 81
Exceeds expectations: Correctly answers all questions 59.26%
Meets expectations: Correctly answers all but one or two
questions 35.80%
Does not meet expectations: Incorrectly answers three or more
questions 5.94%
Panel B: Assessment of a student's ability to employ data
analytics and report key findings
Exceeds expectations and does all of the following: 29.63%
Prepares a professional memo in good form AND
Identifies largest customer and associated revenue and GP AND
Identifies sales as seasonal AND
Identifies Carly Marshall's sales have been declining OR
Identifies Carly Marshall has few sales at week end OR
Identifies Express Grocery is no longer a customer OR
Identifies K&K Quick Mart is no longer a customer OR
Identifies Gabby Bennett greatly surpasses other sales reps OR
Identifies 4 or 5 key customers are in same region OR
Identifies other, more subtle trends in the data
Meets expectations: 61.73%
Prepares a professional memo acceptable form AND
Addresses questions specfically asked by Ivana AND
Identifies at least one key data trend from above
Does not meet expectations: 8.64%

Memo lacks professionalism or is not in good form AND/OR
Does not correctly or adequately address questions asked by
Ivana AND/OR
Does not correctly or adequately address at least one key data
trend from above
Table 3
Results of student survey responses.
Survey item Mean (n = 76) Std Min Max
1. I used a variety of skills to solve this case 6.17 0.97 4 7
2. This project was a engaging and interesting 6.17 0.89 3 7
3. Overall, this project was a good learning experience 6.50
0.64 4 7
4. I have a better understanding of how to analyze data 6.42
0.80 4 7
5. I am more comfortable with using Tableau for data analytics
6.53 0.79 4 7
6. I am more comfortable creating data visualizations in
Tableau than in Excel 5.92 1.18 3 7
7. I have a better understanding of how data analytics and data
visualizations can help make better business decisions 6.38 0.89
4 7
8. I am comfortable creating data visualizations in Tableau 6.29
0.81 4 7
Based on survey response results where “1” denotes “strongly
disagree” and “7” denotes “strongly agree”.
20 The debriefing questionnaire was similar to those found in
the educational case study literature and similar in design and
structure to that of Detzen, Stork
gennant Wersborg, and Zulch (2015).

(2018) 49–59
56
• “I really enjoyed diving deeper into the data. Being able to see
how data can be used to help a business is very cool, and I
would
like to possibly explore it even further.”
• “I like how it has step-by-step analysis and then allows you to
figure more out on your own. Great assignment.”
• “Honestly, I enjoyed this case because I thought the data was
interesting and not too hard for me to complete with only
having a
little exposure to Tableau so far.”
• “I thoroughly enjoyed using Tableau. It was very neat and
interesting. I believe it will be very helpful for future work.”
• “I thought this was a great learning opportunity. I wish we
could have done more cases like this in class for homework.”
• “Overall, it definitely added to my comfortability with
Tableau.”
• “Working with Tableau is a good learning experience.”
4. Case solutions
Solution
s may be obtained by e-mailing the contact author at
[email protected]

Acknowledgements
We would like to thank the two anonymous reviewers and the
editor-in-chief, Natalie Churyk for the thorough feedback and
helpful suggestions. In addition, we would like to acknowledge
the helpful feedback we received from the participants at the
2017
AAA TLC Midyear Colloquium. We would also like to thank
the Accounting Information System and Internal Auditing
students at
Southern Illinois University Edwardsville who enabled us to
pilot test our case study. We would also like to thank graduate
assistants,
Kristina Ingold and Connor Creasey who aided in the many
revisions. Lastly, Amanda Mortimer would like to recognize the
research
funding provided to her as the recipient of SIUE’s Competitive
Graduate Award (CGA), that enabled her to collaborate on this
case
study.
Appendix A. Introduction to data analytics
In this case study, you will gain an understanding of company
data and be asked to transform data into useful information to

aid
in the decision-making process. Big data and data analytic
topics continue to make headlines in a myriad of media outlets.
Big data
refers not only to the quantity of data now available (volume),
but also the variety (form of data), velocity (analysis of
streaming
data), and veracity (uncertainty or quality) of data (IBM Big
Data & Analytics Hub 2017). With roughly 2.5 quintillion bytes
of data
being created each day, and over 90% of all data in existence
created within the last two years, there is now more data than
ever for
companies to capture, secure, analyze, and report. This
digitization and automation across all facets of organizational
processes has
become known as Industry 4.0, or the fourth Industrial
Revolution.
With more companies capturing more data, the market demand
for data analysis continues to grow. Accounting firm PwC,
recently conducted a survey of roughly 2000 industrial
companies across 26 countries and found 33% of companies
have achieved
“advanced digitization”, but 72% expect to do so by 2020 (PwC,

2017). Many companies struggle to process, analyze, and utilize
the
copious amounts of data they are now capturing. PwC expects
companies to spend 5% of annual revenues on Industry 4.0
capabilities,
including robust data analytic technologies, processes and
experienced personnel (PwC, 2017). Recent literature suggests
that the
first obstacle is turning raw data from different sources into
something that can be used to make decisions (Sivarajah,
Kamal, Irani, &
Weerakkody, 2017). The amount of data can be overwhelming
to organize and interpret, and managers can have a hard time
sorting
through the data to determine what is important. Without the
ability to interpret and derive meaning from the influx of data,
it is of
no use. Data analysis requires a different skill set from
traditional financial accounting. It requires individuals to go
beyond line items
in the financial statements and, instead, examine large data sets
to identify trends, make predictions regarding future
performance,
and acquire a better understanding of company data to drive key
business decisions based on empirical evidence. Accountants

are
increasingly being asked to go beyond their traditional roles and
analyze large data sets in order to provide support to
management
(Beaman & Richardson, 2007; Romney & Steinbart, 2015).
It is clear that many companies are still trying to figure out how
to use such large amounts of data to their advantage. Extant
literature describes the importance of education on data
analytics by saying the “human element” is one of the biggest
challenges to
the growth of analytics. In addition, in order to gain the biggest
advantage from analytics, all workers - not just a few analytics
experts - should have basic data analytics training (Tschakert,
Kokina, Kozlowski, & Vasarhelyi, 2016). Without a basic
understanding
of the uses of data analytics, advanced analytics tools are
underutilized, and the benefits are small or nonexistent.
Public accounting firms are pushing for more data analytics
experience from their new hires as digitization of the audit
profession
significantly lags the digitization in industry (Dai & Vasarhelyi
2016; Vasarhelyi, Kogan, & Tuttle 2015). A recent report by big
four

accounting firm Deloitte names hiring workers with a
background in data analytics as one of the best ways to make
the most of the
big data trend. Deloitte has even gone as far as to pair with
universities to create new programs in the area of analytics
(Deloitte,
2017). This is just one of many examples of how businesses are
encouraging employees, as well as students, to obtain an under -
standing of big data.
The Association to Advance Collegiate Schools of Business
(AACSB) is an organization that provides accreditation to
schools in
business and accounting. Schools must meet many minimum
requirements to be accredited by AACSB, including a recent
addition,
AACSB Accounting Standard A7. Accounting Standard A7
requires “accounting degree programs include learning
experiences that
develop skills related to the integration of information
technology and business. Included in these learning experiences
is the
(2018) 49–59

57
development of skills and knowledge related to data creation,
data sharing, data analytics, data mining, data reporting, and
storage
within and across organizations”. More specifically, AACSB
Accounting Standard A7 suggests accounting students should be
able to
comprehend basic information management related to relational
and nonrelational databases, and possess, “knowledge of data
visualization…and interpretation coupled with the ability to
effectively convey data, results, and insights”, further
emphasizing the
increased demand for skills in data analytics for accountants
(AACSB, 2013).
Appendix B. Data visualization software
Data visualization is the presentation of data in graphical
formats. Data visualization helps users of data understand the
data, and
data visualization software enables the user to see and

understand the data in ways that could only previously be done
through the
usage of complex queries and time-consuming manipulation.
Simply examining a huge data set line by line is unlikely to
provide
meaningful information or identify areas of concern. Data
visualization software can create multiple graphs, charts, and
other vi-
sualizations from large data sets so users can quickly display
data in the most efficient and effective manner. The
visualizations can
easily be changed to accommodate new information or to
analyze the data differently. With these graphs, it is easier to
see the big
picture and identify trends and patterns in the data that would
not have been apparent in the data’s original form.
While a variety of data visualization software exists to enable
users to easily create graphical representations of the data, the
price
and capabilities can vary greatly from one software package to
the next. Important capabilities to consider include the types of
data
that can be imported, ease of use, visual capabilities, and ability
to create, share, and present dashboards. Other concerns include

whether the program is cloud-based or stored on the device, as
well as how much maintenance and customization is required.
The Gartner annual report on Business Intelligence and
Analytics Software ranks data visualization software based on
the soft-
ware’s completeness of vision and ability to execute. Tableau
continues to be ranked as a leader in both categories (Gartner,
2017)
(see Fig. 1).
A company in the healthcare industry recently reported that
their adoption of Tableau for data analysis and visualizations
has
saved the company “thousands of hours in redundant data
analysis (Tableau, 2015).” Another company in the healthcare
industry
reported that, “With Tableau, we have eliminated more than
10,000 h of work (Tableau, 2017b).” In addition to increased
func-
tionality, Tableau was chosen as the data visualization software
for this project as it used by many accounting firms and their
clients
and is free of cost to students. In addition, Tableau provides a
plethora of free, easy to access training and how -to videos to

assist users
in learning the software.
Fig. 1. Gartner annual report on Business Intelligence and
Analytics Software (photo taken from www.gartner.com).
(2018) 49–59
58
http://www.gartner.com
Appendix C. Supplementary material
Supplementary data associated with this article can be found, in
the online version, at http://dx.doi.org/10.1016/j.jaccedu.2018.
05.002.
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papers/accounting-accreditation-standard-7.ashx

papers/accounting-accreditation-standard-7.ashx
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value-4-vs-big-data

https://www.pwc%20.com/gx/en/industries/industry-4.0.html
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graph-is-right-for-you
https://www.tableau.com/stories/customer/cleveland-clinic-
%20foundation-saves-hundreds-hours-
tableau?utm_source=Facebook%26utm_medium=%20Social%26
utm_%20campaign=Prospecting-HCOP-HC-ALL
https://www.tableau.com/stories/cus tomer/cleveland-clinic-
%20foundation-saves-hundreds-hours-
tableau?utm_source=Facebook%26utm_medium=%20Social%26
utm_%20campaign=Prospecting-HCOP-HC-ALL
http://refhub.elsevier.com/S0748-5751(17)30195-1/h0110Using
Tableau to visualize data and drive decision-
makingCaseRequirementsAdditional case requirementsTeaching
notesLearning objectivesImplementation guidanceAlternative
implementation guidanceEvidence of efficacyCase
solutionsAcknowledgementsIntroduction to data analyticsData

visualization softwareSuppleme ntary materialReferences

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