Build Visualizations

In this lesson you will create a story to analyze the top late paying customers and forecast the amount outstanding.

At the conclusion of this lesson your Analytical Story will look similar to…

Log on and select your Live Data Source

Launch SAP Analytics Cloud in a Chrome browser.

Lobby

Note: use the URL instead of the Product Switch of SAP Datasphere to navigate to the stand-alone SAP Analytics Cloud tenant.
Login with your user credentials:

Username:

Password: provided by instructor
Once in SAP Analytics Cloud, expand the Navigation Bar >> Stories, under Create New select Canvas.
Select “Classic Design Experience” and click Create.
Click on the “Chart” symbol, to add a Chart element as an object to the story.

Alternatively go to the story top menu and select “Insert” -> “Chart” icon.
Select the SAP Datasphere Live Data connection, your personal SAP Datasphere space and your analytical data set created in the previous lesson.
- Option = “SAP Datasphere Analytical Dataset”
- Connection = “SAPDSP”
- Space = “”
- Dataset = “Advanced AR Model(AR_OPEN_VIEW_ADVANCED)”
Click OK to confirm the selections.

We shall build our first chart to show “Late Days per Customer”.

Insert a Chart.
A new visualization tile will be added, please move that tile as shown in the below image.

Note: Data source “AR_OPEN_VIEW_ADVANCED” is already embedded into the story.
In the Builder pane, select Vertical from Chart Orientation, and add “Late Days” from Measures.
Add “Customer” in Dimensions.

Once the Chart is populated we will sort it by the top 5 Customers with highest late days.

Select More Actions “…” on the chart and follow the path Rank >> Customer >> Top 5 to get top 5 customers with late days.

Adding a boarder to the Chart.

Building Forecast on “Amount in LC”.

Add a filter to the story to read data for specific Quarters.

Select Story Filter/Prompt from Tools.

Note: - If you don’t see Tools >> Story Filter/Prompt in the top navigation, select More then Story Filter/Prompt.
Select Dimensions >> Net Due Date(DTE) >> Filter by Range.
Set the date range for Net Due Date (DTE) and click OK.

Select Type : Fixed

Granularity : Quarter

Quarter : 2020 Q1 to 2020 Q2

Enable Automatic Forecasting.

Select More Actions “…” on the forecast chart, then Add >> Forecast >> Automatic Forecast.

Add a Boarder to the Chart.

Go to Styling as showing in the image and select All Borders under Border.

Link charts to apply filters on the story.

Click More Actions “…” from the “Late Days per Customer” chart, select Linked Analysis and All Widgets in the Story, then click Apply.
Filter by customer on “Late Days per Customer” chart.

Select customer USCU_CM15 and click on Filter icon.

Both charts will be filtered to USCU_CM15 customer.
Remove Filter by deleting the filter on USCU_CM15.

Insert a Chart.
In the Builder pane, select Correlation >> Bubble from Chart Structure.
Select Measures.

X-Axis : “Late Days”

Y-Axis : “Amount in LC”

Dimensions : “Customer”
Change the Color Pallet to red.

At least one more measure is required for the Bubble chart.

Create a Calculation measure to get the count of Documents per customer.

Click + Add Measure from size, then select Create Calculation.
In the Calculation Editor set the following … and click OK.

Type : Aggregation

Name : “Document Count”

Operation : COUNT

Measure : “Amount in LC”

Aggregation Dimensions : “Document number”