Story filters are a feature that allows you to filter the data in a story based on one or more dimensions or measures. You can use story filters to do the following:
They can be applied to all widgets based on the same model. You can choose which widgets are affected by the story filter and which are not.
They can be used to create dynamic titles or text based on the filter values. You can insert filter tokens into titles or text elements to show the current filter values.
They can be used to create input controls that allow users to change the filter values interactively. You can add input controls such as drop-down lists, sliders, checkboxes, etc., to let users select their own filter values.
Story filters cannot do the following:
They cannot be implemented without a model in a template. You need to have a model as a data source for your story before you can apply story filters.
They cannot be used to change dimensions in a widget. You cannot use story filters to swap dimensions in a widget. You have to use the chart builder or the table builder to change dimensions in a widget.
Therefore, the correct answer is They can be applied to all widgets based on the same model, as it is what can be done with story filters. Verified Reference:: Filter Data in Stories

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 Reference: [SAP Analytics Cloud – Datapoint Comments]

An input control is a type of filter that allows you to dynamically change the values of dimensions or measures in your story or application. You can use an input control to filter dimension or measure values and select dimension or measure values for your widgets, such as charts, tables, or geo maps1. For example, you can create an input control that lets you choose which product category or year to display in your chart2.
You cannot use an input control to define a prompt or explore data relationships. A prompt is a filter that is applied to a model before the data is loaded into a story or an application. Prompts allow you to select the data that you want to see in your story or application. You can create prompts in the modeler, not in the story or application3. To explore data relationships, you can use the Smart Discovery feature, which allows you to automatically generate insights and visualizations based on your dat a. You can access Smart Discovery from the context menu of a chart or table widget4.

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 schem
a. 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.

When break grouping is enabled, the sort is applied to the inner dimension of the chart or table, according to the SAP Analytics Cloud Help1. Break grouping is a feature that allows you to sort data points in a chart or table by breaking the grouping of the dimensions in the category axis2. For example, if you have a chart with two dimensions in the category axis, such as Country and Product, and you enable break grouping, you can sort the data points by Product instead of Country2. This can help you compare the performance of different products across countries. You can also choose to sort by measure values or custom order2.
The other options are not correct. Option A. The outer dimension is the dimension that is not affected by the break grouping feature. Option C. The vertical dimension and option D. The horizontal dimension are not relevant terms for break grouping, as it depends on how you arrange the dimensions in the category axis.
1: Apply Smart Grouping to Charts in Analytic Applications | SAP Help Portal 2: Sort Data Points in Charts and Tables | SAP Help Portal

The valid targets for hyperlinks are external websites, SAP Analytics Cloud stories, and SAP Analytics Cloud story pages. External websites are web pages that are outside of SAP Analytics Cloud, such as https://www.sap.com. SAP Analytics Cloud stories are presentation-style documents that use charts, visualizations, text, images, and pictograms to describe dat a. SAP Analytics Cloud story pages are individual pages within a story that contain one or more widgets. SAP BusinessObjects Web Intelligence documents and SAP Analysis for Microsoft Office workbooks are not valid targets for hyperlinks; they are different types of documents that are not supported by SAP Analytics Cloud. Verified Reference: [SAP Analytics Cloud – Hyperlinks]

A calculated measure is a type of measure that is derived from an expression or formula based on existing measures or dimensions. You can use calculated measures to perform various calculations on your data, such as ratios, percentages, differences, etc. However, some calculated measures may result in errors or invalid values when the denominator is null or zero. For example, if you try to calculate the profit margin as (Profit / Revenue) * 100, and the revenue is zero, you will get an error. In such cases, SAP Analytics Cloud displays a symbol instead of a value for the calculated measure. The symbol that is displayed when the denominator is null or zero is # (hash sign). Therefore, the correct answer is #, as it is the symbol that is displayed when the denominator is null or zero in a calculated measure. Verified Reference:: Create Calculated Measures

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 dat a. 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 for this 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.
Reference:
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]

You can define thresholds in the model or in the story. Thresholds are rules that apply conditional formatting to measures based on certain criteria, such as values, ranges, or percentages. You can define thresholds in the model to apply them to all stories that use the model, or you can define thresholds in the story to apply them to a specific widget or page. You cannot define thresholds in the input control or in the page; these are different types of elements that can be used in a story. Verified Reference: [SAP Analytics Cloud – Thresholds]