README.md

Exercise 1 - Creating Your First Story

Objective: Develop a basic understanding on how to create visualizations within SAP Analytics Cloud.

Estimated Time: 20 mins

Exercise Description: You want to visualize your company's performance over time, and find your first insights.

Key Features:

• Understand how to use the Builder Panel
• Create a variety of different charts to illustrate key relationships within your data

⚠️Disclaimer When completing exercises, some data values in the screenshots may not match what you see on your screen. This is because the dynamic time filters that were applied at the time the screenshots were taken is different from the current system date.

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🚩As a business analyst for the BestRun company, we are interested in a business intelligence dashboard to utilize our finance and shipping data to guide business decision making. We can do this by creating a story.

1. Click Create Your First Story

ℹ️Welcome to Start Your Story Page!

On this page, users can choose to import their own data, run a smart discovery on their data, add a responsive, canvas, or grid page, or start their story using a template. We are interested in exploring our data and the dimensions and measures we can analyze before we create a dashboard.

2. Click Responsive

🚩Let’s start by adding in some charts.

3. Click Insert (Click More on the top toolbar if you don't see Insert)

4. Click Chart

ℹ️The data we will be using was already uploaded by a colleague in the Finance department. Let us access this model from the Public/TechEd folder in our tenant.

5. Click Public

6. Click TechEd 2021

7. Click ANA260_ORDER_FINANCE

ℹ️Welcome to the Builder Panel!

The Builder Panel is a place where you can create your visualizations. The chart area on your responsive page will remain empty until a measure and dimension are selected from the Builder Panel. It will dynamically update depending on the visualization that you are trying to create.

We have just added an empty chart to our story and now we want to start adding measures and dimensions to build our chart into a visualization for business insights!

8. Click Add Measure

9. Scroll untill you find Sales Revenue

10. Click Sales Revenue

11. Click Inside the Builder Panel to Collapse the Measure Selection Drop Menu

12. Click Add Dimension

13. Scroll untill you find Region

💡Within the Dimension Selection Menu, a hierarchy icon is displayed next to hierarchaldimensions. Dimensions with attributes can be further expanded within the menu.

14. Click Region

15. Click Inside the Builder Panel to Collapse the Measure Selection Drop Menu

🚩We have now created our first bar chart using the Builder Panel.

16. Resize the chart to be wider

⚠️Quality Check! Does our story page look like the screenshot?

17. We can easily change the layout of our story page. Click and drag the Right Lane to the Top

🚩Let's start adding in some additional charts. First, we are interested in the gross margin breakdown across our different products.

18. Click Bottom Pane

19. Click Insert (Click More on the top toolbar if you don't see Insert)

20. Click Chart

21. Click Add Measure

22. Scroll to find Gross Margin

23. Click Gross Margin

24. Click Inside the Builder Panel to Collapse the Measure Selection Drop Down Menu

25. Click Add Dimension

26. Scroll to find Product

27. Click Product

28. Click Inside the Builder Panel to Collapse the Measure Selection Drop Down Menu

🚩We have now created our second bar chart using the Builder Panel. However, our data can be further transformed to extract more valuable business insights. Let’s change the hierarchy level so we can see gross margin for different Product categories.

🚩We can drill down on the Product dimension to get more information from our bar chart. You can also drill down on charts via the Builder Panel as a designer or by clicking on the bar and drilling down.

29. Click Set Drill

30. Click Level 2

We can now see gross margin by each product category (Accessories, Clothing, Footwear), but we want to explore our data further and generate insights from the additional Workout Usage dimension in our model.

31. Under Color Click + Add Dimension/Measure

32. Scroll untill Workout Usage is Visible

33. Click Workout Usage

34. Click Inside the Builder Panel to Collapse the Measure Selection Drop Down Menu

🚩Our bar chart is now divided in each product category by its Workout Usage. Using Color in charts is an effective way of mapping additional dimensions into a visualization. We can change our Chart Type to better visualize the dimensions we have selected.

35. Click Bar/Column Tile

36. Click Stacked Bar/Column

🚩We want to scale our chart so that the distribution of workout usage in each product category is easily comparable in percentages of the total.

37. Click Show Chart as 100%

38. Resize the chart to be Wider

⚠️Quality Check! Does the Stacked Bar Chart in your story show up like this?

🚩Our chart visualization now displays for us the proportional distribution of gross margins in each Product Category based on their Workout Usage. This enables us to quickly analyze the contribution of the Workout Usage dimension within a Product Category

🚩We now want to analyze how our gross margin has been performing over time. Let us build a chart with a time dimension to display this data.

39. Click Insert (Click More on the top toolbar if you don't see Insert)

40. Click Chart

41. Click + Add Measure

42. Scroll to find Gross Margin

43. Click Gross Margin

44. Click Inside the Builder Panel to Collapse the Measure Selection Drop Down Menu

45. Click Add Dimension

46. Scroll to find Order Date

47. Click Order Date

48. Click Inside the Builder Panel to Collapse the Measure Selection Drop Down Menu

🚩SAP Analytics Cloud immediately recognized our time dimension and created an upright chart orientation as per best practices. However, our chart currently shows an aggregation of all gross margins in our data set. Next, we want to apply a dynamic time filter for the year to date range and change the drill level to show months as the granularity of bars.

🚩We have many options on filtering or drilling down on a dimension simply by hovering over the dimension in builder panel.

49. Click Filter

50. Click Current

51. Click Year under To Date

🚩SAP Analytics Cloud offers users the ability to choose from a variety of dynamic time filters to quickly customize their charts to their business needs. We are using a year to date filter on our chart, so our data is filtered to begin on the start of the year 2021 until today.

🚩Let us Set Drill on our dimension. Currently our bar chart is aggregating data over all time, however we are more interested in seeing performance per month for the current year.

52. Click Set Drill

🚩Our hierarchy levels correspond to levels of granularity. In SAP Analytics Cloud, we dynamically provide various levels of time granularity (i.e. YQM, YHQM, YM). Currently, this chart is set to a YQM hierarchy with the first level set to aggregate over all time, so we want to select level 4 to reach monthly granularity

53. Click Level 4

🚩We have just created a chart with a time dimension using a Year to Date filter to organize our visualization. Next, we want to learn more about the trend of Gross Margin from our chart.

⚠️Please note your data will look different from this chart's values due to the dynamic date filter.

54. Resize the chart to be wider

🚩We can look at the trend of Gross Margin from our chart by adding a trendline by using the context menu.

55. Right Click on the chart to open the Context Menu

56. Click Add

57. Click CGR (Compound Growth Rate)

🚩We use the CGR added to the chart that compared to look at our compound growth rate in the year. If the CGR is negative it could be alarming information for the business user

🚩Let us add a table to our story to examine our Gross Margin contribution by each Sales Manager. Since Sales Manager is a high cardinality dimension with a lot of members, it is recommended to view this data in a table.

58. Click Insert (Click More on the top toolbar if you don't see Insert)

59. Click Table

60. Under Rows Click + Add Measures/Dimensions

61. Scroll untill Product and Sales Manager is visible

62. Click Product

63. Click Sales Manager

64. Click inside the Builder Panel to Collapse the Measure/ Dimension Selection Drop Down Menu

🚩We can see that a table has been created to track Sales Managers. We can choose to expand the Product column to sort our table by Product Category contributions by each Manager. However, our table measure is currently set to Discount. Let’s change it to Gross Margin.

65. Return to the Builder Panel. Click Filter on Account Column

66. Deselect Discount

67. Select Gross Margin

68. Click OK

🚩We have created a table to show contributions of Sales Manager to Gross Margin; however, this value is an aggregate over the entire period spanning the model. We would like to breakdown on Order Date to better interpret the yearly contributions of each Sales Manager to Gross Margin

69. Under Columns Click + Add Measures/Dimensions

70. Scroll untill Order Date is Visible

71. Click Order Date

72. Click inside the Builder Panel to Collapse the Measure/ Dimension Selection Drop Down Menu

⚠️Quality Check! Does your table have the Product, Sales Manager, and Gross Margins columns?

🚩There has been an Order Date field added to our table. If we expand on all, Gross Margin will be separated into yearly sums. We want to see our Gross Margin % in our table but we currently do not have that measure in our data model. We can create the Gross Margin % measure as a calculation with the Sales Revenue and Gross Margin measures

🚩We may be looking for more insights from our data and can do so by creating a calculation!

73. Click the More Icon for Account

74. Click Add Calculation

ℹ️Welcome to the Calculation Editor!

The Calculation Editor allows you to create calculations for use in a chart or table. There are various types of calculations that a user can create which include:

1. Calculated Measures: Perform a calculation on one or more measures

2. Restricted Measures: Restrict the data from a measure so that it excludes certain members of one or more dimensions

3. Difference From: Find the difference in a measure's value between two points in time for a single time dimension

4. Aggregation: Create an aggregation such as sum, count, count dimensions, max, and max

5. Date Difference: Calculate the difference between two-time dimensions

6. Dimension to Measure: Create a measure by converting a dimension to measure.

We will cover calculations in more detail for business analytics use cases in our Section 8 - Calculations and Blending Deep Dive. You can jump off to this section to learn more.

75. Click Calculated Measure

76. Click the formula field and enter "gro"

77. Click ["ANA260_ORDER_FINANCE": Gross_Margin]

78. Type in "/" to indicate we want to divide in our calculation

79. Type in "Sal"

80. Click ["ANA260_ORDER_FINANCE":Sales_Revenue]

81. Name the measure Gross Margin %

82. Click OK

🚩Now let’s use our newly made calculation in our table and remove the previous measure.

83. Click Filter on Account in Columns

84. Deselect Gross Margin

85. Click OK

🚩Now that we have our desired measure, let’s expand the Order Date column to see our values on a yearly basis.

86. Click > (All) to Expand the Order Date Dimension

🚩We want to hide the all column that aggregates Gross Margin %.

87. Right Click the All Order Date Column

88. Click Hide Column

🚩Our table should look like this screenshot now. Since our calculation is a percentage, we will now change the formatting of our values to improve our table visualization.

🚩We can easily change the formatting and representation of our measures and calculations.

89. Click Story Calculations

90. Click Formatting

91. Deselect Use Unit of Underlying Measures

92. Change Scale to Percentage

93. Change Decimal places to 0

94. Click OK

⚠️Quality Check! Does our table look like this screenshot? We have now formatted our chart so the % symbols for gross margin are indicated in the subtitle. This cleans up the table visualization.

🚩Let us shift our focus back to our dashboard layout. We want to now add some KPIs that stand out for story viewers.

95. Select Top Lane

🚩Since this lane is in now at the top of our dashboard, let us add some easily viewable KPIs as numeric point charts in our story. Numeric point charts are a chart visualization that display the total of a measure and are best suited for highlighting key business KPIs. They can be filtered so the KPI describes a specific context relevant to the business user.

96. Click Insert (Click More on the top toolbar if you don't see Insert)

97. Select Chart

98. Click Indicator

99. Click Numeric Point

100. Click Add Measure

🚩Let us use Gross Margin as our first KPI.

101. Scroll untill Gross Margin is visible

102. Click Gross Margin

103. Click Inside the Builder Panel to Collapse the Measure Selection Drop Down Menu

🚩We should add a date filter on our KPI, so the context is more relevant to a business analyst looking for actionable insights. Let us filter data for the current year.

104. Click Add Filters

105. Click Order Date (Member)

106. Click the Expand icon

107. Click 2021

108. Click OK

🚩You have now created a numeric point chart that displays Gross Margin filtered for only data in 2021.

109. Decrease the size of the Numeric Point Chart

🚩Let us use SAP Analytics Cloud's duplicate chart functionality to easily create our other KPIs.

110. Click the More icon

111. Click Copy

112. Click Duplicate

⚠️Quality check! Has your dashboard updated with a copied KPI chart like this screenshot?

ℹ️We want to create a new KPI of Sales Revenue like our first chart of Gross Margins. Since we duplicated the KPI, our previously applied date filter will be automatically applied to our new KPI. Let us now change the measure of our second KPI.

113. Deselect the Gross Margin measure for your new chart by clicking Remove

114. Click Add Measure

115. Scroll until Sales Revenue is visible

116. Click Sales Revenue

117. Click Inside the Builder Panel to Collapse the Measure Selection Drop Down Menu

🚩Now that we are satisfied with our second KPI for Sales Revenue, let us duplicate this chart again to create a KPI that calculates average sales revenue.

118. Click the More icon

119. Click Copy

120. Click Duplicate

🚩We currently do not have a measure for our average sales revenue by store in our model. Hence, let us create a calculation to track this metric on our dashboard.

121. Remove Sales Revenue as a Measure (for the duplicate chart)

122. Click Add Measure

123. Click Create Calculation in Add Measure

🚩We want to calculate the average sales revenue by store for our company. This will require an aggregation of all sales revenue averaged by number of stores. We can create this in the Aggregation Calculation Type.

124. Select Aggregation as Calculation Type

125. Click Expand for Operation

126. Scroll till AVERAGE is Visible

127. Click AVERAGE

128. Click Expand for Measure

129. Click Sales Revenue

🚩Here we are selecting the aggregation dimension that will be used to calculate our average. Since we want average sales revenue by store, we should change this dimension to Store.

130. Click Expand for Aggregation Dimensions

131. Scroll till Store is Visible

132. Click Store

133. Rename the calculation to Avg Sales Revenue

134. Click OK

⚠️Quality Check! Do your numeric point charts have these values and measures on your story? Please note that your time chart may look different from this screenshot due to the dynamic date filter on YTD.

🚩At this stage, you should save your first story.

135. Click File

136. Click Save

137. Click Save

137. Save your story in My Files as ANA260_ Your Initials

138. Click OK

🚩 You can also save your story by pressing Ctrl + S on your keyboard

ℹ️You have completed Creating Your First Story!

Please continue with the next section Linked Analysis and Input Controls. We will also improve the styling of this dashboard in Section 4 - Theme and Style!

Summary

You have completed the entire Create Your First Story section!

You are now able to:

• Understand how to use the Builder Panel
• Create a variety of different charts to illustrate key relationships within your data