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© SAP AG Page 1


SAP Analytics Cloud


Data Analysis

Nitin Kalé

Modified May 2019
Dr. Ed Lindoo


Many courses at SAP University
Alliances member schools use ERP
Simulation Game to introduce students
to the role of integrated business
processes using a business simulation
game. This game simulates a
commodity market wherein teams
have to plan, procure, produce and sell
products in a competitive

The goal is to strategize and run their
company for profit maximization. The
game is played in the SAP ERP
system while an external simulator
simulates the dynamic market and all
the variables that influence the game.
This exercise can be used during or at
the end of the game to analyze game

Before you use this case study, you need
to have an SAP Analytics Cloud account.
Please follow the instructions later in this
case study to request an SAP Analytics
Cloud account.

The human visual system has evolved to be particularly good at recognizing patterns. Data
visualization has become a standard analytical tool which capitalizes on the ability of humans to
recognize patterns within massive quantities of multi-dimensional data generated by business
information systems. Many scientific studies have led to the creation of visualization models that
utilize human perception and cognition.

When the number of dimensions is small, we can use standard graphing techniques for
visualization e.g. ​bar charts, line charts, histograms, pie charts ​and​ scatter plots.

When the number of dimensions is large, there are several novel techniques for visualizing such
data. They are categorized into the following major areas ​1​ – For more information on these
visualization techniques, please refer to the journal reference in the footnote.

A. Pixel-oriented Techniques
a. Space filling curves
b. Recursive pattern
c. Snake-Spiral
d. Circle segments

B. Geometric Projection Techniques
a. Parallel coordinates
b. Scatter plot matrix
c. Hyperbox
d. Trellis display
e. Self-organizing maps

C. Icon-based Techniques
a. Star glyphs
b. Color icons
c. Stick figures
d. Chernoff faces

D. Hierarchical and Graph-based Techniques
a. Dimensional stacking
b. Cone trees
c. Mosaic plots
d. Fractal foam

1. The ERPSim game is played by teams over several rounds (up to 8 rounds of 30 virtual days
each). They sell up to six products at a time from a possible 12 products that the market

1 Keim D. A., Kriegel H.-P. ​Visualization Techniques for Mining Large Databases: A
Comparison ​, Transactions on Knowledge and Data Engineering, Vol. 8, No. 6, Dec. 1996, pp.

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Data Visualization

Data Visualization for ERPsim

consumes. The products are all muesli cereal​2​ in various flavors and box sizes. The teams must
forecast demand, run MRP, procure, produce, price and market their products for sale.

2. Figure 1 shows the entire cash to cash cycle in the game. The transactions in bold are decision
points that teams must make and execute. They are considered strategic in nature. The
transactions that are gray are considered operational in nature. They are automated by the
simulator. Additionally, teams can run analytical reports at various points in the game to
monitor and strategize.

Figure 1

3. Data from an actual game have been extracted from SAP ERP and stored in an Access
database. Then queries have been written to report important findings. The results have been
exported to Excel.

4. Your job is to analyze these results as requested in the following assignment

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We will now use SAP Business Analytics.

1. Launch Google Chrome. If you don’t have it, install it as it’s the only browser that work

2. Click the link below to go to SAP Cloud Analytics
(Note: if your browser does not default to Chrome, you will need to copy the URL and
paste it into Chrome)

3. You now see a screen that looks like this:

The first time you come here you’ll need to click the Register button to get the following screen:

Be sure to register with your Nova email address. Any email other than Nova are wiped from the
system on a weekly basis!

4. After you register, you’ll get a screen that looks like this:

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Using SAP Business Analytics

Note that it sends an email to your Nova email account for verification.

5. Here’s the email that you should get. Just click on the button to activate your account.

You’ll be taken to a screen that looks like this:

Click the Continue button to get the following screen.

You’re taken to this profile page where you can tweak things if you want to (optional).
Now, log out from the profile page and go back to the sign in page:

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Sign in with your Nova email and password that you created.


6. Once the system loads, in the top left corner of the screen click on the 3 little bars (Next to


a. Click ​Create, ​then ​Story

b. Next, click on Add a Canvas Page

Next click on ​Chart

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c. Models have already been created for us and are found in the Public folder.

Click on the Public folder and you’ll see a screen that looks like this:

Now click on Models

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Select ERPsim Dataset

d. You are now ready to begin charting!
7. Choosing ​measures​ and ​dimensions

a. What is a ​measure​? A measure is a field on which calculations can be made. These
are fields of business interest for analytics. e.g. revenue, profit, quantity sold. The
calculations can sum, min, max, average, count etc. Measures are also called ​key
figures​ or ​facts​.

b. What is a ​dimension​? A dimension is reference information about a measure. It
provides context for the measures. E.g. customer, time, product. ​Revenue by
customer​ is an example of how you would report a measure by a dimension.

Figure 2

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1. Interface
a. Look towards the top right of the screen. See the boxes labeled Comparison, Trend,

Distribution, etc.? These allow you to change to various types of charts. Select the bar

b. Add Revenue to the Measures and Product to the Dimensions
c. You will now see a screen that looks like this:

d. Play around with some of the controls like sorting. Hover over the Product line within

dimensions. You’ll see a filter icon pop up. Change the filter to look only for 1kg items.
e. Add team to color and see what happens.
f. Explore, have fun and get used to the system before moving on.

2. We are now ready to manipulate and visualize this data

a. Several charting options are available for visualization on the right side of the
screen – bars, lines, pies, geographic, scatter/bubble, maps, radar, tag cloud etc.

b. Using the appropriate charting technique, answer the following questions. Hints are
provided for each question.

NOTE: Log off and back on before you begin the exercises below to ensure that all the filters and
settings you applied above in testing are gone!

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Note, each question is worth 10 pts.

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Analytics Cloud 1 – Revenue by Team

Question:​ Which team had the highest revenue? What was the revenue?

Time​ 10 min

Hint: Use a column chart. From Measures, drag Revenue into Y-Axis, from Dimensions, drag
Team into Y-Axis. Find the sort tool next to the database name and change Sort of revenue to
descending. Use Save to save the visualization as Q1. You do not need to submit a screen shot,
just place your answers below.

Analytics Cloud 2 – Revenue by Product

Question:​ What product had the highest revenue? What was the revenue? Time​ 10 min
Zeist​ 10 Min.

Hint:​ Use a ​column​ chart. Y-Axis – ​Revenue​, X-axis – ​Product. Save As​ Q2. You do not need to
submit a screen shot, just place your answers below.

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Analytics Cloud 3 – Revenue by Team and Round

Question:​ Display the trend of revenue over rounds for each team. Time​ 10 min

Hint:​ Use a line chart. Y-Axis – Revenue, X-Axis – Round, Legend Color – Team. For this
answer you do need to submit a screen shot. Alt-PrntScrn on some computers will copy the screen
to the clipboard, you can then paste it into this document. If that doesn’t work you can save this as
Q3. Then use the back arrow to get the main screen where you see Q3 has been saved. Click on
that and when it comes up you can right click on it and save the picture to your computer. Once
it’s saved to your computer you can launch it and typically copy/paste into this document. just
place your answers below. If that doesn’t work, try a screen capture program.

Analytics Cloud 4 – Revenue by Team and Product

Question: ​What is the market share of each team by product? Time​ 10 min

Hint: ​Use a Column chart. X-Axis – Revenue, Y-Axis – Product, Trellis Rows: Team, Save as
Q4. For this answer you need to submit a screen shot. A screen shot of just the first team is all
that is needed here.

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Analytics Cloud 5 – Revenue by Distribution Channel and Product

Question:​ Are there any products that don’t sell in specific distribution channels? Time​ 10 min

Hint: ​Use a heat map. Area Color – Revenue, Area Name – Distribution Channel & Area Name2
– Product. Save as Q5. For this answer you need to submit a screen shot.

Analytics Cloud 6 – Price by Product and Team

Question: ​What was the highest price paid for 1kg Raisin Muesli? Which team sold the most
expensive Muesli? What did team MM sell the Muesli for? Time​ 10 min

Hint:​ Use a column chart. Y-Axis –Price, X-Axis – Team. Legend Color – Product. In the
resulting chart, add a rank of top 1 for product. Save as Q6. A screen shot is not needed here, just
your 3 answers.

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Analytics Cloud 7 – Quantity by Team and Product

Question:​ Which team sold the most quantity of muesli? For that team, what was the most sold
product and for how much? Time​ 10 min

Hint:​ Use a tree map (under Heat Map). Area Weight – Quantity, Area Name – Team. Click on
the team with the highest number and select filter. Next, add Product to Area Name. What was
the largest quantity that this team sold? What was the name of this product? No screen shot
necessary, just your two answers. Save as Q7.

Analytics Cloud 8 – Revenue and Price by Product

Question:​ What three products have high price and high revenue? Time​ 10 min

Hint:​ Use a Bubble chart. Measures: Y-axis: Quantity. X-axis: Price. Color: Product, Bubble
Width: Revenue. Be sure there are no filters applied. Save as Q8. No screen shot necessary, just
your three answers.

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Analytics Cloud 9 – Highest revenue on a day

Question:​ Show the days on which individual teams did not have any revenue. What team made
the highest revenue on a single day (which round)? Time​ 10 min

Hint: ​Use a Heat Map. Measures: Color: Revenue. Dimensions: X Axis: Round and Team.
Dimensions: Y Axis: Day. Save as Q9. Here we need a screen shot of your results which should
look like a lot of light green and dark green squares. Don’t forget to write your answer to the
second part of the question.

Analytics Cloud 10 – Highest revenue for a product on a single day

Question: ​What product on what day and round brought the highest revenue (for which team)?

Time​ 10 min

No Hint! ​Save as Q10. Screen shot not needed, just your answers.

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