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Regis-SAPBusinessObjects_Fishbanks_Student_Final1.doc

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Product

SAP Business Analytics

Level

Undergraduate

Graduate

Beginner

Focus

Data Analysis

Authors

Ed Lindoo, Ph.D.

Version

1.0

Motivation

Many courses at SAP University Alliances member schools use SAP Business Analytics Cloud to visually show data.

The goal is for you to take a deep dive into the provided data and analyze trends and patterns over time.

Data Visualization

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 – 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

Data Visualization for NOAA fish data from 2005-2015

Using SAP Business Analytics

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 well.

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

3. Enter the username [email protected] (Note: boc stands for Business Objects Cloud)

4. Enter the password RegisSAP1 (Note: this is case sensitive. Be sure to use upper/lower case as indicated!)

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

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a. Click Create, then Story

b. Next, click on Add a Canvas Page

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Next click on Chart

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c. Use the drop down to select the NoaaFishData model, then Click OK

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d. You are now ready to begin charting!

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6. 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.

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Figure 1

7. 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.

The 10 exercises/questions begin on the next page. Be sure in all answers to indicate the units such as $, lbs, year, tons etc.

Exercises

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Business Analytics 1 – Highest revenue year for Atlantic Cod

Question: What year had the highest total revenue for Atlantic Cod? What was the amount of the revenue?

Hint: Use a bar/column chart. In Measures select Revenue, select Species in Dimensions and select year in the Color area. Hover over Species within the Dimensions area and click on the filter, then search and filter for Cod and select Atlantic Cod. At the top right of the chart you have some options. Make sure you sort year lowest to highest.

Place your answer as well as a screen shot of your chart here.

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Business Analytics 2 – Catch by Year

Question: What year produced the most pounds of fish? What was the amount of fish in that year?

Hint: Use a heat map. Measure = Pounds, Dimension = Year.

Place your answer as well as a screen shot of your chart here.

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Business Analytics 3 – Best Revenue Producing Industries

Question: Display the top 5 revenue producing industries (Herring, Cod, etc)?

Which of these industries has the highest overall total revenue? What was its revenue?

Hint: Use a donut chart found under “More”, Use Revenue for measure, Species for Color. Choose top 5 for options

Place your answer as well as a screen shot of your chart here.

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Business Analytics 4 – Price per pound

Question: What year had the highest price per pound for King Crab? What is the amount in that year?

Hint: Use a line chart. Measure = Revenue, Dimensions = Year and Species. Remember to filter Species for King Crab only. To get the price per pound you need to create a calculated field. To do so, within Measures click Add a Measure, then click Create a New Calculation called “Profit Per Pound”. The formula is Revenue/pounds. Click ok, you will now see revenue and your new calculation listed in the Measures area. Double hint……if you did this right the price per pound in 2009 was $3.85

Place your answer as well as a screen shot of your chart here.

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Business Analytics 5 – Branded Spiny Lobster contribution

Question: What percent of the total revenue for the years 2006 – 2015 did the Branded Spiny Lobster contribute? What was the amount of the total revenue during this period?

We saw in exercise #3 that the top revenue producing industry was the American Lobster. But there are other types of Lobster fished each year. Putting aside the American Lobster, display the other species and their total contribution for the 10 years -- 2005-2015.

Hint: Use a pie chart. Measures = Revenue, Color=Species. Filter for all the lobsters EXCEPT the American Lobster. Hover over the pie chart to see the revenue

Place your answer as well as a screen shot of your chart here.

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Business Analytics 6 – Rockfish Analysis

Question: Of all the species of Rockfish, what was the 3rd highest producing fish species and revenue for the years 2005-2015? What was the lowest of the TOP Seven (7)?

Hint: This is similar to exercise #1. Use a pie chart and apply appropriate filters and sorting techniques show the top 7 revenue producing Rockfish species.

Place your answer as well as a screen shot of your chart here.

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Business Analytics 7 – Shark! Shark!

Question: In terms of pounds, what is the most fished Shark species? How many pounds of this specie were taken during the years 2005-2015?

Hint: Use a Heat map. Filter for top 5 sharks

Place your answer as well as a screen shot of your chart here

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Business Analytics 8 – Best Price per Pound

Question: What Shark produced the highest price per pound? How much was the price per pound? What was the lowest price per pound paid for a Shark? What Shark species had the lowest price per pound?

Hint: Use a Merimekko chart. This is quite similar to Exercise #4, just using a different chart. Don’t forget to sort by top n.

Place your answer as well as a screen shot of your chart here.

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Business Analytics 9 – Projecting your future

Background: You are in the Cod fishing business in the north Atlantic, off the New England coast. As we saw in exercise #1, this past year was the worst ever…..there are basically no Cod fish left! Your future and your family’s future is at stake! What are you going to do?

Question: Graphically compare the past 10 years of Cod fishing in the Atlantic versus the Pacific and make a case for whether, and why, you should keep your one boat where it is currently on the Atlantic, or move your family and your boat to the Pacific.

1. What has been the 10 year trend of Pacific Cod versus Atlantic Cod?

2. What were the Pacific Cod revenues in 2015?

Hint: Use a colorful bar chart works well, but you can test the waters with any chart that makes sense. For example, a line charge containing both trends of the chart.

Place your answer as well as a screen shot of your chart here.

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Business Analytics 10 – Tough Decisions!

Background: Turns out you have a lot of family in New England and your spouse and kids do now wish to move to the Pacific with you so you can continue to catch Cod. All you know is fishing so you’re going to stay in New England and fish, but what are you going to fish for? Do some research on the web and find out what’s happening in the area, what are other fishermen doing and write a one paragraph essay as to what you are going to start fishing for (it can’t be Lobster nor Shrimp because your boat isn’t that type of boat, it’s for fish!). You need to support this decision with either with data you find on the Web (be sure to provide a full citation for the data), or by using the supplied NOAA data. Show this graphically in question #2 below.

Questions:

1. Even though you’re not going to become a Lobsterman, from your research you have discovered why lobster are being harvested more than ever. Explain why more and more American Lobster are being harvested each year and show this graphically (years 2005-15) in a yearly colored bar chart. What was the total 2015 Revenue for American Lobster?

2. There is one fish in your data that is mentioned quite often on the Web. It just so happens that more of these are moving north into the now warmer New England waters. So Cod fishermen are beginning to fish these. Produce a chart showing the yearly revenues of this fish from 2005-2015. What was the 2015 total revenue for this fish?

No Hint!

#1

Place your answer as well as a screen shot of your chart here.

#2

Place your answer as well as a screen shot of your chart here.

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INTRODUCTION TO SAP BUSINESS ANALYTICS Cloud�

This case study introduces SAP Business Analytics Cloud to use data visualization to analyze NOAA fish data.

Trellis Dimension

Color Dimension �n

Various chart types

Dimensions

Chart

Measures

� 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. 923-938.

© 2008 SAP AG

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