C_SACS_2321 Exam Dumps - SAP Certified Application Associate - SAP Analytics Cloud Story Design

This is one of the story guidelines recommended by SAP Analytics Cloud. According to the course material1, “When designing your stories, keep them as simple as possible. In general, it is easier for users to consume story content if it is present in smaller bits rather than have a few large stories with many pages to navigate.” The other options are not mentioned as guidelines in the course material.

1: Introducing SAP Analytics Cloud Story Design | SAP Training 2

The correct answers are C. Have a clear message and D. Use corporate branding standards. These are some of the guidelines that SAP recommends you follow when you create a story. According to the course material1, “Your current reporting and dashboardstandards will suffice for SAP Analytics Cloud stories. And if you do not have reporting or dashboard standards, this is the perfect time to create them.” The course material also suggests that you should “have a clear message and purpose for your story” and "use corporate branding standards to ensure consistency and professionalism"1.

The other options are not mentioned as guidelines in the course material. Option A. Use grouping is a feature that allows you to group data points in a chart or table, but it is not a general design principle. Option B. Avoid pie charts is a common advice for data visualization, but it is not specific to SAP Analytics Cloud stories.

1: Introducing SAP Analytics Cloud Story Design | SAP Training 2

Data point comments are a feature that allows you to add comments to specific data points in a story. You can use data point comments to provide additional information, context, or feedback on the data. You can also reply to, edit, or delete existing comments. Data point comments are supported for the following models:

• Import models
• Planning models
• Blended models

Data point comments are not supported for live models, such as SAP S/4HANA live model or BPC live model. Therefore, the correct answer is Import planning model and Blended model, as they are the models that support data point comments. 

Data point comments are comments that you can add to a specific value in a table or a comment widget. They are similar to commenting on a single cell in Microsoft Excel. Data point comments are associated with the models, which means that they will appear in any story that uses the same model and has the same value in a table or a comment widget1.

Data point comments can be added to the following models:

• Import planning model: This is a model that you create by importing data from a file or a database. You can use this model for planning scenarios, such as budgeting, forecasting, or what-if analysis. You can enable data point comments forthis model by selecting the Allow Data Point Comments option in the model properties2.
• BPC live model: This is a model that you create by connecting to a SAP Business Planning and Consolidation (BPC) system. You can use this model for real-time planning and analysis with BPC data. You can enable data point comments for this model by selecting the Allow Data Point Comments option in the model properties3.

Data point comments cannot be added to the following models:

• SAP S/4HANA live model: This is a model that you create by connecting to a SAP S/4HANA system. You can use this model for real-time analysis with SAP S/4HANA data. However, this model does not support data point comments, because it is read-only and does not allow any changes to the data4.
• Blended model: This is a model that you create by blending data from two or more models. You can use this model for combining and analyzing data from different sources. However, this model does not support data point comments, because it is derived from other models and does not have its own data.

References:

1: Using Data Point Comments - SAP Learning 2: Creating an Import Planning Model - SAP Learning 3: Creating a BPC Live Model - SAP Learning 4: Creating an SAP S/4HANA Live Model - SAP Learning : [Blending Data from Multiple Models - SAP Learning]

Chart scaling is a feature that ensures that you have a meaningful display of values across multiple charts in a story. By default, charts are not scaled, which can lead to incorrect data analysis, particularly if users are not paying attention to the actual values displayed in the chart1.

Chart scaling is applied to the following:

• Specific page: Chart scaling is applied to all of the charts on a page, but the scaling may be different for the same measure on different pages, because the scaling factor is calculated separately for each page1.
• Specific measure: Chart scaling is applied to a specific measure in a chart, and it affects all the charts that contain that measure on the same page. You can exclude charts from the scaling by selecting the chart and choosing Exclude from Scaling in the context menu1.

Chart scaling is not applied to the following:

• All measures: Chart scaling is not applied to all the measures in a story, only to the ones that are selected for scaling. You can select which measures to scale by choosing Scale Measures in the context menu of any chart on a page1.
• All pages: Chart scaling is not applied to all the pages in a story, only to the ones that have scaling enabled. You can enable or disable scaling for a page by choosing Enable Scaling or Disable Scaling in the context menu of any chart on a page1.

A section is a way of organizing a story into different parts based on a dimension. A section creates a separate page for each member of the dimension, and displays the same widgets on each page with the data filtered by the section dimension1. For example, if you create a section based on the Country dimension, you will have a page for each country in your data, and the charts and tables on each page will show only the data for that country.

The other options are not correct because:

• Value Driver Tree: This is a widget that allows you to create a graphical representation of how different drivers affect a key performance indicator (KPI). You can use this widget to perform simulations and what-if scenarios on your data2. However, this widget does not create a chart for each member of a dimension.
• In-Cell Charts: These are mini charts that are displayed within table cells to show the relative values of measures. You can use this feature to enhance the readability and analysis of your data3. However, this feature does not create a chart for each member of a dimension.
• Trellis: This is a feature that allows you to split a chart into multiple smaller charts based on one or more dimensions. You can use this feature to compare and contrast different segments of your data4. However, this feature does not create a separate page for each member of a dimension.

References:

1: Creating Sections - SAP Learning 2: Using Value Driver Trees - SAP Learning 3: Using In-Cell Charts - SAP Learning 4: Using Trellis Charts - SAP Learning

When you are adding a calculation to a table, you can choose from two options: Single or Multiple. The option determines how many new columns are added to the table based on the calculation. The options are:

• Single: Adds one new column to the table with the calculation result for the selected dimension member. For example, if you select Soft Drinks and choose Single, you will get one new column with the calculation result for Soft Drinks only.
• Multiple: Adds multiple new columns to the table with the calculation result for each dimension member. For example, if you select Soft Drinks and choose Multiple, you will get three new columns with the calculation result for Soft Drinks, Juice, and Alcohol.

Therefore, the correct answer is Selected dimension member, as it is the option that the new column is added to when you choose Single. Verified References:

• : Create Calculations in Tables

• Points of Interest Layer - Sets of geographical data that can be added to a geo map and analyzed with reference to business data from a model. For example, you can add points of interest layer that shows the locations of your customers or stores on a geo map.
• Choropleth/Drill Layer - Applies blocks of shading to different geographical locations based on the value of the selected measure. For example, you can add choropleth/drill layer that shows the sales revenue by country or region on a geo map.
• Feature Layer - Uses external data from valid service URLs. This data is layered on top of your existing geo map to provide additional context. For example, you can add feature layer that shows the traffic conditions or weather information on a geo map.
• Flow Layer - Shows the connection between two locations based on the value of the selected measure. For example, you can add flow layer that shows the trade volume or migration patterns between countries or regions on a geo map.
• Heat Map Layer - Uses color to visualize the data density of the selected measure. For example, you can add heat map layer that shows the population density or crime rate by area on a geo map. Verified References: [SAP Analytics Cloud - Geo Maps]

The SAP Digital Boardroom supports engaging with a remote audience through annotations and screen sharing. Annotations allow users to highlight or draw on the screen using different colors and shapes, which can help to emphasize key points or explain complex concepts. Screen sharing allows users to share their screen with other participants who join the digital boardroom session via a web browser, which can help to facilitate collaboration and communication. Data Analyzer and story editing are not features that support engaging with a remote audience; they are features that allow users to analyze data or modify stories in the digital boardroom. Verified References: [SAP Analytics Cloud - Digital Boardroom]