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SAP Datasphere is a data source that does not require a model to be created in SAP Analytics Cloud. You can use a SAP Datasphere connection to access or import data directly into your story, with no need for a SAP Analytics Cloud model to be created1

SAP Business Warehouse, SAP S/4HANA, and SAP BusinessObjects Web Intelligence document are data sources that require a model to be created in SAP Analytics Cloud. You cannot access or import data from these sources directly into your story, but you need to create a model in SAP Analytics Cloud using the connections to these sources234

The story page types that are imported into the SAP Digital Boardroom builder are responsive and canvas. Responsive pages are designed to adapt to different screen sizes and orientations, making them suitable for different devices and scenarios in the digital boardroom. Canvas pages are designed for desktop browsers and fixed layouts, making them suitable for large screens and presentations in the digital boardroom. Grid pages are not imported into the digital boardroom builder; they are designed for tabular data analysis and printing. Verified References: [SAP Analytics Cloud - Digital Boardroom]

The link type determines how the data from the primary and secondary models are blended in a story. There are three link types: Primary, All, and Intersection1.

Primary: Only the data from the primary model that matches the data from the secondary model is displayed. This is equivalent to an inner join in SQL.

All: All the data from both models is displayed, regardless of whether they match or not. This is equivalent to a full outer join in SQL.

Intersection: Only the data that exists in both models is displayed. This is equivalent to an intersection in set theory.

In this case, the link type that returns what data is Intersection, because it only shows the data that is common to both models, such as Customer A and Customer B. Customer C and Customer D are excluded because they do not exist in both models.

The correct answers are B. Public and D. Embedded. These are two of the dataset types that SAP Analytics Cloud supports, according to the SAP Help Portal1. A public dataset is a standalone dataset that is stored in SAP Analytics Cloud and can be found in a folder location on the Files page1. An embedded dataset is a dataset that is saved within a story and does not appear in the Files list1. You can convert an embedded dataset to a public one if you want others to be able to use it1.

The other options, A. Import and C. Live, are not dataset types, but data source types. You can import data from a file or other data source to create a dataset or a model2. You can also use live data from a source system to create a model, but not a dataset2.

1: About Datasets and Dataset Types | SAP Help Portal 3 2: Choose Between Datasets and Models | SAP Help Portal

Datapoint comments are stored in the data model, not in the widget, page, or story. This means that datapoint comments are visible across different stories that use the same model, and they are preserved when a story is duplicated or exported. Verified References: [SAP Analytics Cloud - Datapoint Comments]

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]

A public dataset is a type of dataset that is shared among different stories. You can use public datasets to create stories or blend data with models. A public dataset has the following properties:

It can be shared among different stories. You can use public datasets in multiple stories without having to import them again.

It cannot be converted to a model. You cannot convert a public dataset to a model. If you want to create a model from a public dataset, you have to import it as a private dataset first.

Its data is not structured in a star schema. A public dataset does not have any predefined dimensions or measures. It only has columns and rows of data.

Its data source cannot be changed. You cannot change the data source of a public dataset after you import it. If you want to update the data in a public dataset, you have to import a new file.

According to the SAP Help Portal1, SVG (Scalable Vector Graphics) is the recommended image file type for optimal story performance in SAP Analytics CloudStory Design. SVG is a vector-based format that can scale to any size without losing quality or clarity. SVG images also have a smaller file size than other image formats, such as JPEG, PNG, or BMP, which are raster-based formats that store pixel data. Raster images can lose quality or become blurry when scaled up or down, and they also have a larger file size than vector images. Therefore, using SVG images can improve the loading speed and responsiveness of your stories, as well as the visual appearance of your images2.

The design options that are available when you create a new story are optimized and classic. Optimized design option allows users to create stories using an intuitive and simplified interface, with fewer options and more automation. Classic design option allows users to create stories using a full-featured and flexible interface, with more options and more control. CSS and style are not design options when you create a new story; they are concepts related to web development and formatting. Verified References: [SAP Analytics Cloud - Story Design Options]

To apply the formatting of the year 2024 to the years 2025 and 2026, you need to use the level option Self and Descendants in the styling rules. This option applies the formatting to the selected member and all its lower-level members in the hierarchy1. In this case, the selected member is the year 2024, and its lower-level members are the months, quarters, and half years that belong to 2024. The formatting will also be applied to the years 2025 and 2026, and their lower-level members, because they are at the same level as 2024 in the hierarchy.

The other level options are:

Self: This option applies the formatting only to the selected member, not to any other members in the hierarchy1. In this case, the selected member is the year 2024, and the formatting will not be applied to any other years or lower-level members.

Self and Siblings: This option applies the formatting to the selected member and all its siblings, which are members at the same level in the hierarchy1. In this case, the selected member is the year 2024, and its siblings are the years 2025 and 2026. The formatting will be applied to these three years, but not to their lower-level members.

Self and Children: This option applies the formatting to the selected member and its immediate children, which are members one level below in the hierarchy1. In this case, the selected member is the year 2024, and its immediate children arethe quarters and half years that belong to 2024. The formatting will be applied to these members, but not to any other years or months.