C_SAC_2402 SAP Certified Associate - Data Analyst - SAP Analytics Cloud Questions and Answers

In SAP Analytics Cloud, enabling Advanced Mode in story design is necessary for activities that involve custom development or advanced integration, such as adding JavaScript to a button for custom interactions or behaviors, and adding a custom widget, which allows for the integration of bespoke visualizations or functionalities that are not available out-of-the-box. These features require a deeper technical engagement, hence the need for Advanced Mode.

References:

• SAP Analytics Cloud Help Documentation: Advanced Story Design Features
• SAP Analytics Cloud User Guide: Custom Widgets and JavaScript Functions

To total several income and expense accounts using the account type property, the "Aggregate To" configuration option in the advanced formula must be used. This option allows you to aggregate data based on a specific dimension or property within your model, such as the account type. By using "Aggregate To," you can sum up the values of various income and expense accounts into broader categories, facilitating more high-level financial analysis and reporting.

References:

• SAP Analytics Cloud Help Documentation: Advanced Formulas and Calculations
• SAP Analytics Cloud User Guide: Aggregating Data Using Account Properties

In a planning data model in SAP Analytics Cloud, the Date and Version dimensions are included by default. The Date dimension is essential for time-based planning and analysis, while the Version dimension allows for the creation and management of different data scenarios, such as budget, forecast, and actuals. These dimensions provide a foundational structure for planning activities within the model.

References:

• SAP Analytics Cloud Help Documentation: Planning Data Model Basics
• SAP Analytics Cloud User Guide: Understanding Default Dimensions in Planning Models

The Optimized Design Experience in SAP Analytics Cloud features several enhancements to facilitate story creation and exploration, including the Undo button, Grid pages, and the Explorer mode. The Undo button provides the ability to revert actions, enhancing the editing process. Grid pages allow for precise layout control of story elements. Explorer mode offers an interactive way to discover insights within the data, using dynamic visualizations and natural language queries.

References:

• SAP Analytics Cloud Help Documentation: Optimized Design Experience Features
• SAP Analytics Cloud User Guide: Exploring Data with Optimized Design Experience

For datasets that extract data from external systems like SAP Business Warehouse (SAP BW), SAP Analytics Cloud provides the capability to schedule updates on a regular basis. This feature ensures that the dataset within SAP Analytics Cloud remains up-to-date with the latest changes from the SAP BW system, without the need for manual reimport or creating a new dataset. Scheduled updates can be configured to run at specific intervals, automating the data refresh process.

References:

• SAP Analytics Cloud Help Documentation: Scheduling Data Refresh
• SAP Analytics Cloud User Guide: Automating Dataset Updates from External Sources

To apply a styling rule only to countries in a table with a hierarchy of Country, Region, and City in SAP Analytics Cloud, you must use the "Self" level option. This option ensures that the styling rule is applied specifically to the level of the hierarchy representing countries, without affecting the styling of regions, cities, or any other hierarchical levels.

References:

• SAP Analytics Cloud Help Documentation: Styling Hierarchical Tables
• SAP Analytics Cloud User Guide: Hierarchical Styling Options

When using a live connection in SAP Analytics Cloud, data security is defined and managed within the source system. This approach leverages the existing security protocols and permissions set up in the source system, ensuring that data governance and access controls remain consistent and are centrally managed. Users accessing data through SAP Analytics Cloud with a live connection will be subject to the same security constraints and permissions as if they were accessing the data directly from the source system. This integration ensures a unified security model, simplifying administration and ensuring data security and compliance.

The Just Ask feature in SAP Analytics Cloud utilizes natural language processing (NLP) to interpret user queries formulated in natural language. This feature allows users to ask questions about their data in a conversational manner, and the system intelligently interprets and responds with relevant visualizations and insights, making data analysis more accessible and intuitive.

References:

• SAP Analytics Cloud Help Documentation: Just Ask Feature and NLP
• SAP Analytics Cloud User Guide: Leveraging Natural Language Processing

Connections and data preparation

When using a live connection in SAP Analytics Cloud, the data remains stored in the source system. This means that no data is imported or replicated into SAP Analytics Cloud; instead, it is accessed and analyzed in real-time directly from the source system. This approach ensures that the most current data is always used for analysis and that data governance and security policies of the source system remain in control.

References:

• Live Data Connections to SAP S/4HANA | SAP Help Portal1
• SAP Analytics Cloud Connection Guide2
• SAP Analytics Cloud Data Connections - InsightCubes

In the context of SAP Analytics Cloud, when using a live connection to connect to a data source, the data remains stored in the source system. This setup means that SAP Analytics Cloud directly queries the data in its original location, without importing or copying it into the SAP Analytics Cloud environment. This approach is advantageous for several reasons, including maintaining a single source of truth, reducing data redundancy, and ensuring data is always up-to-date without the need for synchronization processes. Live connections are particularly useful for real-time or near-real-time data analysis and reporting, providing insights based on the most current data available without the overhead of data replication.

References:

• SAP Analytics Cloud documentation and user guides typically emphasize the benefits and use cases of live connections, highlighting how they maintain data in the source system to ensure real-time data access and analysis.
• SAP training materials for Data Analysts using SAP Analytics Cloud, including study guides and official certification resources, explain the technical and practical aspects of live connections, including where data is stored and how it is accessed.
• Best practice guides for SAP Analytics Cloud, often available through the SAP Community or SAP Knowledge Base, provide insights and recommendations on setting up and using live connections, reinforcing the concept that data stays in the source system.

When the SAP Analytics Cloud (SAC) modeler removes the first three characters from a public dimension imported from a source system, this change impacts Stories that use this dimension. Specifically, any visualizations, calculations, or filters within those stories that rely on the original dimension values may need to be adjusted to account for the change. This modification does not affect the source system or public datasets directly, but it can impact how the data appears and behaves in stories that use the modified dimension.

References:

• SAP Analytics Cloud Help Documentation: Modifying Dimensions
• SAP Analytics Cloud User Guide: Impact of Dimension Changes on Stories

SAP Analytics Cloud supports two primary types of data connections: Live Data Connection and Import Data Connection. Live Data Connection establishes a direct link to the data source, allowing real-time data access without replicating the data into SAP Analytics Cloud. This is ideal for scenarios where up-to-the-minute data is crucial, and data volume is large. On the other hand, Import Data Connection involves copying data from the source into SAP Analytics Cloud, which is suitable for scenarios where data doesn't change frequently, or there's a need for data transformation and enrichment within SAP Analytics Cloud.

References:

• SAP Analytics Cloud Help Documentation: Data Connections Overview
• SAP Analytics Cloud User Guide: Live Data vs. Import Data Scenarios

For designing a new story in SAP Analytics Cloud where the size and position of widgets need to adjust dynamically for different devices and screen sizes, the Responsive page type should be used. Responsive pages automatically adapt to the screen size of the device they are viewed on, providing an optimal viewing experience across desktops, tablets, and smartphones.

References:

• SAP Analytics Cloud Help Documentation: Responsive Design in Stories
• SAP Analytics Cloud User Guide: Building Responsive Pages

If SAP Analytics Cloud interprets a 'Year' column as a measure instead of a dimension, it should be changed to a dimension to ensure it is treated as a calendar year. This adjustment can be made within the model or dataset settings, where the column's role can be switched from a measure (quantitative value) to a dimension (qualitative value). Treating 'Year' as a dimension allows it to be used appropriately in time-based analyses, such as trends over time, without being aggregated like a numerical measure.

In SAP Analytics Cloud Data Analyzer, you can use various data sources to analyze your data in a tabular, ad-hoc reporting environment. Among the supported data sources are SAP HANA views, which provide real-time access to HANA calculations and data models; SAP Datasphere models, which allow you to leverage data across your enterprise landscape within SAP Datasphere; and SAP BusinessObjects Universes, which enable semantic layers built on various data sources for complex reporting needs.

References:

• SAP Analytics Cloud Help Documentation: Data Analyzer
• SAP Analytics Cloud User Guide: Supported Data Sources for Data Analyzer

To update the data in a model based on an import connection, two main approaches can be used:

• Refresh the story:This action forces SAP Analytics Cloud to reload the data for the visualizations in a story, pulling in the most recent data available in the model. This is a manual process initiated by the user.
• Schedule the import:This option allows users to set up a recurring data import schedule, ensuring the model is regularly updated with the latest data from the source system. This automated process helps maintain data freshness without manual intervention.

Both methods ensure that the story reflects the most current data, accommodating changes in the transaction data of the model's data source.