Lumira Exercise PDF

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Tutorial work to work with Lumira....

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SAP Lumira Cloud

SAP LUMIRA CLOUD NITIN KALÉ, UNIVERSITY OF SOUTHERN CALIFORNIA

OBJECTIVE Use data visualization to analyze ERP simulation game data using SAP Lumira Cloud.

ACTIVITIES     

Sign up for free SAP Lumira Cloud Import and prepare data Perform data cleansing and harmonization Create data visualizations Publish (share) results

SOFTWARE PREREQUISITES  

Internet Explorer 9 or higher SAP Lumira Cloud account (free) (the instructions in this exercise are for the cloud version of SAP Lumira, not for SAP Lumira desktop software)

SCENARIO 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 environment. 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 data.

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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 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

DATA VISUALIZATION FOR ERPSIM

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. 923-938. Nitin Kale © 2014

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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 consumes. The products are all muesli cereal2 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.

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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. We will now use SAP Lumira Cloud to acquire ERPSim game data, and to visualize and discover any interesting trends. 5. Launch Internet Explorer. 6. Go to the URL http://cloud.saplumira.com

7. Sign up for a free account. SAP Lumira Cloud provides two editions: Free Edition and Enterprise Edition. The Free Edition does not expire and provides individual users with 1GB of 2 http://en.wikipedia.org/wiki/Muesli 3 Léger, P.-M., Robert, J., Babin, G., Pellerin, R. and Wagner, B. (2007), ERPsim, ERPsim Lab, HEC Montréal, Montréal, Qc.

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storage. The Enterprise Edition provides multiple GBs of shared storage and the ability to manage user access and permissions. 8. Acquiring ERPSim data a. Figure 2 shows the entry screen. Here you can create new datasets, see existing datasets

and check the share status of datasets.

Figure 2

b. Click Create Dataset, Browse for a new file c. Browse for the Sales Data file (provided by your instructor). Click OK d. You should see a preview of the data being acquired. 9. 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. c. Click on the Wrench icon

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d. Since the values in Round, Day are numeric, Lumira has incorrectly identified them as measures (in the left panel). e. Click on the sum next to Round and Day. f. Change to Dimension. g. Change the aggregation of Price to Max. h. Click Acquire. 10. Interface a. Click on Sales Data dataset b. Lumira automatically creates some visualizations on its own. This is called Visual Discoveries! c. Click on Explore. This allows you to create your own visualizations and save them for future reference. You can share them as well. d. See Figure 3 for the SAP Lumira cloud interface. Click on List view (left side of screen) .

e. Explore the various panels and tools.

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Measures

List view

Chart

Visualization View

Dimensions

Axes control

Figure 3

11. 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. Nitin Kale © 2014

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

Question 1: Which team had the highest revenue?_ _What was the revenue?_ Hint: Use a column chart. From Measures, drag Revenue into Y-Axis (under Data), from Dimensions, drag Team into X-Axis & Values. In Y-axis (in the chart itself), change Sort of revenue to descending (use the arrow). Use Save As to save the visualization as Q1.

Question 2: What product had the highest revenue?_ _What was the revenue? _______ Hint: Use a column chart. Y-Axis – Revenue, X-axis & Values – Product. Save As Q2

Question 3: Display the trend of revenue over rounds for each team. Hint: Use a line chart. Y-Axis – Revenue, X-Axis – Round, Values & Color – Team. Sort the Round in ascending order (use arrows in the chart itself). In the legend for team, you can focus the analysis by selecting one of the teams (e.g. R). Save as Q3.

Question 4: What is the market share of each team by product? Hint: Use a Stacked Bar chart. Y-Axis – Revenue, X-Axis – Product, Values and Color: Team, Save as Q4

Question 5: Are there any products that don’t sell in specific distribution channels? _________________________ Hint: Use a heat map. Y-axis – Distribution Channel, X-axis – Product Values & Color – Revenue. Save as Q5

Question 6: What were the highest prices paid for various products per team? ____________ Which team sold the most expensive Muesli? _______________

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Hint: Use a Size Comparison chart. Y-Axis –Product, X-Axis – Team. Values & Size – price. In the resulting map, move the Price delimiters in the chart to filter out bubbles of small size (price) until you reach the highest. Save as Q6

Question 7: Which team sold the most quantity of muesli? For that team, what was the most sold product? Hint: Use a tree map. Value & color – Team, Size – Quantity. Remove any data in the Split By and Size fields. Then Split by: Product. Save as Q7

Question 8: What three products have high price and high revenue? _______ Hint: Use a Bubble plot. Measures: Y-axis: Quantity. X-axis: Price. Values & Color: Product, Size: Revenue. Save as Q8

Question 9: Show the days on which individual teams did not have any revenue. What team made the highest revenue on a single day (which round)? Hint: Go to Analyze. Trellis - Rows - Round, X-axis – Team, Y-axis – Day. Data points – Revenue. Type – Bar, Mode- Comparison, Color – Team, Size – Revenue. Save as Q9 Use the revenue filter slider to focus in the highest revenue.

Question 10: What product on what day and round brought the highest revenue (for which team)? No Hint, Save as Q10

Question 11: Create an animated chart that shows Revenue by Team. Animation should be done over round.

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12. Share some of your visualizations with your colleagues using the share feature. 13. Log out of SAP Lumira Cloud

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