CS代考 LWYVA185) with the permission from SAS Australia to use and publish for tea

UNSW Business School/
Information Systems and Technology Management
SAS Viya for Learners – SAS Visual Analytics Workbook 1
Analyzing Data Using SAS Visual Analytics

3-2 Lesson 3 Analyzing Data Using SAS® Visual Analytics
SAS Visual Analytics Workbook:
Compiled/Modified By Date SAS Visual Analytics Jacky Mo Sep. 2021 SAS Viya for Learners
All the SAS Visual Analytics Workbooks will help the students to learn and gain experience and skills in data preparation; data exploration; creating reports; and constructing dashboard.
Reference:
This learning material is extracted from SAS® Academic Hub (LWYVA185) with the permission from SAS Australia to use and publish for teaching purpose at the University of Wales.
File Name:
SAS Viya for Learners – SAS Visual Analytics Workbook 1
Copyright:
This learning material is created for Business Analytics courses offered by the School of Information Systems and Technology Management, the University of Wales, Sydney, Australia.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

Lesson 3 Analyzing Data Using SAS® Visual Analytics
3.1 Working with Data Items …………………………………………………………………………………………..3-4
Demonstration: Working with Data Items ………………………………………………………………. 3-66 Practice …………………………………………………………………………………………………………..3-111
3.2 Exploring Data with Charts and Graphs…………………………………………………………………..3-12
Demonstration: Exploring Data: Part 1………………………………………………………………….. 3-16 Practice …………………………………………………………………………………………………………… 3-28 Demonstration: Exploring Data: Part 2………………………………………………………………….. 3-31 Practice …………………………………………………………………………………………………………… 3-36
3.3 Creating Data Items and Applying Filters ………………………………………………………………..3-37
Demonstration: Creating Data Items …………………………………………………………………….. 3-45 Practice …………………………………………………………………………………………………………… 3-54 Demonstration: Applying Filters …………………………………………………………………………… 3-60 Practice …………………………………………………………………………………………………………… 3-71
3.4 Performing Data Analysis ……………………………………………………………………………………….3-73
Demonstration: Analyzing Data …………………………………………………………………………… 3-75 Practice …………………………………………………………………………………………………………… 3-81 Demonstration: Adding Data Analysis …………………………………………………………………… 3-88 Practice …………………………………………………………………………………………………………… 3-94
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.
3.1 Working with Data Items 3-3

3-4 Lesson 3 Analyzing Data Using SAS® Visual Analytics
3.1 Working with Data Items
Modify formats
Other changes
Business Scenario: Customers
Modify aggregations
Copyright © SAS Institute Inc. All rights reserved.
SAS Visual Analytics Methodology: Analyze
Modify properties
Create data items
Discover trends
Add filters
Discover patterns
Copyright © SAS Institute Inc. All rights reserved.
Explore relationships
Create models*
* Creating, testing, and comparing models can be accomplished with SAS Visual Statistics and SAS Visual Data Mining and Machine Learning.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

SAS Data Studio
SAS Visual Analytics
SAS Visual Analytics App
3.1 Working with Data Items 3-5
SAS Data Studio versus Visual Analytics
SAS Cloud Analytic Services (CAS)
Copyright © SAS Institute Inc. All rights reserved.
SAS Visual Data Studio uses a CAS table as input and creates a CAS table as output.
SAS Visual Analytics uses a CAS table as input and creates a report that can be viewed in Visual Analytics or the SAS Visual Analytics app. Any changes to data made in Visual Analytics apply to the report only and do not affect the CAS table.
Beginning with Visual Analytics 8.3, report data views can be created to save and apply settings for a data source. A data view acts as a template for any settings that are modified, including data property changes, data source filters, hierarchies, geography data items, calculated items, and more. A data view does not update the CAS table. If the view is updated, your reports are not automatically updated with the new settings.
Data views are saved separately from your reports. If you create a data view in one report, you can apply it to other reports that use the same data source.
Data views can be shared by an application administrator so that other users can apply them to the data source.
A data source can have a default view as set by an application administrator. You can also set the default view for yourself. A default data view is automatically applied anytime that you add the data source to a report.
For more information about data views, see “Working with Data Views in Reports” in the SAS Visual Analytics: Working with Report Data documentation.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-6 Lesson 3 Analyzing Data Using SAS® Visual Analytics
Working with Data Items
This demonstration illustrates how to modify data item properties (name, format, aggregation) in Visual Analytics.
1. From the browser window, sign in to SAS Viya.
2. In the upper left corner, click (Show list of applications) and select Explore and Visualize.
SAS Visual Analytics appears.
3. Click All Reports.
a. Navigate to the Courses/YVA185/Basics/Demos (Marketing) folder.
b. Double-click the VA1- Demo3.1 report to open it.
4. In the left pane, click Data.
The Data pane contains a list of data items from the CUSTOMERS_CLEAN table.
5. Verify that Customer ID and Order ID appear in the Category group, because the data type was
changed to character in SAS Data Studio.
Note: Character and datetime data items appear as categories in Visual Analytics.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

6. Verify that the new column created in SAS Data Studio (Loyalty Num) appears in the Category group.
7. Verify that the new columns created in SAS Data Studio (Days to Delivery and Profit) appear in the Measure group.
Note: Numeric (double) data items appear as measures in Visual Analytics.
3.1 Working with Data Items 3-7
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-8 Lesson 3 Analyzing Data Using SAS® Visual Analytics
Note: Cost and Retail Price were renamed in SAS Data Studio to Unit Cost and Total Revenue, respectively. Those new names are not reflected because Visual Analytics displays labels, not data source names.
8. Modify properties for a data item, Date Order was Delivered.
a. In the Category group, right-click Date Order was Delivered.
b. Select Format  MMMYYYY (MONYY7).
c. Next to Date Order was Delivered, click (Edit properties).
d. In the Name field, enter Delivery Date and press the Enter key.
9. Modify properties for a data item, Discount in percent of Normal Total Retail Price.
a. In the Measure group, next to Discount in percent of Normal Total Retail Price, click (Edit properties).
b. For the Aggregation field, select Average.
c. In the Name field, enter Discount and press Enter.
10. Modify the aggregation for a data item, Days to Delivery.
a. In the Measure group, next to Days to Delivery, click (Edit properties).
b. For the Aggregation field, select Average.
c. In the Name field, enter Average Days to Delivery and press Enter.
11. Rename data items.
a. In the Category group, next to Date Order was placed by Customer, click
properties).
b. In the Name field, enter Order Date and press Enter.
c. In the Measure group, next to Cost, click (Edit properties).
d. In the Name field, enter Unit Cost and press Enter.
e. In the Measure group, next to Quantity Ordered, click (Edit properties).
f. In the Name field, enter Quantity and press Enter.
g. In the Measure group, next to Retail Price, click (Edit properties).
h. In the Name field, enter Total Revenue and press Enter.
12. Create a data view.
a. At the top of the Data pane, next to the table name, click (Actions) and select Save data view.
b. For the Name field, verify that CUSTOMER_CLEAN_View_1 is specified.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3.1 Working with Data Items 3-9 c. In the Description field, enter Modified data item properties (renamed, changed formats,
changed aggregations)..
d. Click Save. 13. Save the report.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-10 Lesson 3 Analyzing Data Using SAS® Visual Analytics
Practice Scenario: Employees
View table
Modify formats
Other changes
Modify classifications
Copyright © SAS Institute Inc. All rights reserved.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

1. Working with Data Items
3.1 Working with Data Items 3-11
Open the browser and sign in to SAS Viya.
Open the VA1- Practice3.1 report from the Courses/YVA185/Basics/Practices (HR) folder. View the data items in the Data pane and answer the following questions:
What is the classification of Employee ID? Manager at 1. level?
Answer: ________________________________________________________________ What does the Frequency data item represent?
Answer: ________________________________________________________________ Change the classification for Manager at 1. level to Category.
Change the format for Annual Salary to Dollar13.2.
Rename the following data items:
Employee ID
Employee Name
Manager at 1. level
Manager ID
Number of Employees
Note: Click (Actions) and select Refresh EMPLOYEES_CLEAN at the top of the Data pane to collapse the data item properties.
Save the report.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-12 Lesson 3 Analyzing Data Using SAS® Visual Analytics
3.2 Exploring Data with Charts and Graphs
Business Scenario: Customers
Focus group
Range of profits
Order Type
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3.01 Activity
Sign in to SAS Viya. Open the VA1- Activity3.01 report (in the /Courses/YVA185/Basics folder).
What is the average of Days to Delivery?
Which factor is the most related to Days to Delivery?
Which country has the highest average for Days to Delivery?
Copyright © SAS Institute Inc. All rights reserved.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

This report uses an automated explanation object to explore Days to Delivery. The automated explanation object determines the most important underlying factors for a specific response variable.
For more information about the automated explanation object, see “Working with Automated Explanation Objects” in the SAS Visual Analytics: Working with Report Content documentation.
Note: The automated explanation object is discussed in more detail in the SAS Visual Analytics 2 for SAS Viya: Advanced course.
3.2 Exploring Data with Charts and Graphs 3-13
Objects: Graphs (Descriptive)
Use a histogram to view the distribution of
a single measure.
Copyright © SAS Institute Inc. All rights reserved.
Use a box plot to view information about the variability of the data and extreme values.
The histogram contains a series of bars that represent the number of observations (or percentage of all observations) for a measure that fit in a specified value range (or bin). The shape of the distribution can be affected by the number of bins specified for the histogram.
Note: If you use the default number of bins, then the minimum and maximum values on the histogram might not match your actual data values. However, if you specify the number of histogram bins, then the minimum and maximum values on the histogram match your actual data values exactly.
The size and location of the box indicate the range of values between the 25th and 75th percentile (or the interquartile range). The diamond marker inside the box indicates the mean value, and the line inside the box indicates the median value. You can modify options to display outliers in the plot. Outliers are data points whose distance from the interquartile range are more than 1.5 times the size of the interquartile range. The whiskers (lines protruding from the box) can indicate either minimum and maximum values of the plot or the range of values outside of the interquartile range but close enough not to be considered outliers. If there are a large number of outliers, the range of outlier values is represented by a bar colored to represent the number of values inside the outlier range (as seen above).
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-14 Lesson 3 Analyzing Data Using SAS® Visual Analytics
Objects: Graphs (Descriptive)
Use a bar chart to compare summarized data for the following:
Nominal values
Time series data
Parts of a whole
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nstitute Inc. All ri
ghts reserved.
A bar chart displays data aggregated by the distinct values of a category. By default, the bars are sorted by descending order of the value of the first measure. For ranked bars, the data is sorted based on the values of the rank. Stacked bar charts enable you to compare totals for each category, as well as totals for all categories. However, comparing segments is difficult, and when there are many segments in the chart, it is difficult to read. To see relative differences (parts of a whole) in a bar chart, select Normalize groups to 100% for the Group scale option.
Note: Nominal values are categories whose data has no particular order.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3.2 Exploring Data with Charts and Graphs 3-15
3.02 Multiple Choice Question
Which graph would help you determine whether a measure is normally distributed?
a. distribution plot
b. box plot
c. histogram
d. normality plot
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Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-16 Lesson 3 Analyzing Data Using SAS® Visual Analytics
Exploring Data: Part 1
This demonstration illustrates how to use the automatic chart to explore data and modify roles and options for charts and graphs in Visual Analytics.
1. From the browser window, sign in to SAS Viya.
2. In the upper left corner, click (Show list of applications) and select Explore and Visualize.
SAS Visual Analytics appears.
3. Click All Reports.
a. Navigate to the Courses/YVA185/Basics/Demos (Marketing) folder.
b. Double-click the VA1- Demo3.2a report to open it.
4. Turn off automatic graph titles.
a. In the upper right corner, select  Settings.
b. On the left side of the window, select General under SAS Visual Analytics.
c. Scroll down to Default titles for new objects.
d. For Graphs, change Automatic title to No title.
e. Click Close.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

5. Create an automatic chart.
a. In the left pane, click Data.
b. Drag Profit from the Data pane to the canvas.
The automatic chart functionality determines the best way to display the selected data.
A histogram is used to display the distribution of profits.
c. In the right pane, click Roles.
A histogram accepts two roles, Measure and Frequency.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.
3.2 Exploring Data with Charts and Graphs 3-17

3-18 Lesson 3 Analyzing Data Using SAS® Visual Analytics
d. For the Frequency role, select FrequencyFrequency Percent. The histogram is updated to use frequency percent for the Y axis.
e. In the right pane, click Options.
1) Expand the Object group.
2) In the Name field, enter Distribution of Profit.
Note: The Automatic title setting was turned off for Graph objects in an earlier demo. You can turn it on for this graph by selecting Automatic title, or you can create a custom title by selecting Custom title.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3.2 Exploring Data with Charts and Graphs 3-19
f. In the upper right corner of the histogram, click (Maximize) to view additional details. A table of data values is displayed at the bottom of the chart.
g. Click the highest bar in the graph.
h. Scroll through the table to find the highlighted row.
A majority of the products ordered are low-profit items, in the $0 to $25 range. Also notice that more than 20% of items result in a loss. Why is this problem occurring? Are these products ordered from a similar product area, geographical area, or order type? Could the costs be too high in these areas? What can we do to reduce costs?
i. In the upper right corner, click (Restore).
6. Create a crosstab.
a. In the left pane, click Objects.
b. Drag the Crosstab object, from the Tables group, to the bottom of the canvas.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-20 Lesson 3 Analyzing Data Using SAS® Visual Analytics
c. In the right pane, click Roles.
d. For the Rows role, select AddOrder Type and click OK.
e. For the Measures role, select FrequencyProfit.
The Roles pane should resemble the following:
Note: The Measures role is required for the crosstab object. The crosstab should resemble the following:
Profits are much lower in the internet and catalog channels. A company-wide policy mandates that we need to try to improve profits for orders through these channels.
f. On the Roles tab, for the Columns role, select Add  Continent Name and click OK.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3.2 Exploring Data with Charts and Graphs 3-21 The updated crosstab should resemble the following:
g. In the right pane, click Options.
h. Expand the Totals and Subtotals group.
i. Select the Totals check box.
By default, totals are added to rows and columns.
j. Next to the Totals field, select Columns.
k. For the Background color field, click (Select a color).
l. Select Pale blue.
m. For the Format field, verify that (Bold) is selected.
Copyright © 2021, the School of ISTM, UNSW Sydney, Australia. ALL RIGHTS RESERVED.

3-22 Lesson 3 Analyzing Data Using SAS® Visual Analytics
The updated crosstab should resemble the following:
Profits are much lower in North America than in Europe. Because our corporate office is located in North America, we would expect higher profits. Also notice the loss in Africa for internet sales. Why is this loss occurring? Is this due to start-up operations (for example, building distribution facilities in Africa)? Are the losses consistent over time or has this changed over time?
7. Change the crosstab to a bar chart.
a. Right-click the crosstab and

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