C_SAC_2421 SAP Certified Associate - Data Analyst - SAP Analytics Cloud Free Practice Exam Questions (2025 Updated)

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

Table formulas in SAP Analytics Cloud are used to perform cell-based calculations within a story. These formulas can be applied directly to table cells, allowing for customized calculations that are specific to the data presented in the table. This feature is particularly useful for ad-hoc analysis and when specific calculations are needed that are not covered by predefined measures or dimensions.

References:

SAP Analytics Cloud Help Documentation: Using Table Formulas

SAP Analytics Cloud User Guide: Cell-Based Calculations in Stories

In Data Analyzer, users can perform various tasks to analyze their data, including filtering data and drilling down on data. Filtering allows users to narrow down the dataset to focus on specific subsets of data, enhancing the analysis's relevancy. Drilling down provides the ability to explore data at a more granular level, revealing deeper insights into the data points and trends within the larger dataset.

References:

SAP Analytics Cloud Help Documentation: Data Analyzer Usage

SAP Analytics Cloud User Guide: Filtering and Drilling Down in Data Analyzer

In SAP Analytics Cloud, data concatenation can be performed on Embedded datasets, Standalone datasets, and Imported data models. This process involves combining data from multiple sources or tables into a single dataset or model, providing a unified view of the data. This is particularly useful for analyses that require a comprehensive dataset compiled from various data sources.

References:

SAP Analytics Cloud Help Documentation: Working with Datasets

SAP Analytics Cloud User Guide: Concatenating Data in Models and Datasets

A blank planning version in SAP Analytics Cloud can be created within the Version Management feature. This area of the platform allows users to manage different versions of their data, such as budgets, forecasts, and what-if scenarios. Creating a blank version provides a clean slate for planning activities, without pre-existing data, enabling users to start fresh with their assumptions and inputs.

References:

SAP Analytics Cloud Help Documentation: Version Management in Planning

SAP Analytics Cloud User Guide: Creating New Versions for Planning

Collapsing the hierarchy in a story can help limit the refresh time, as it reduces the amount of data that needs to be processed and displayed at any given time. By presenting data at a higher aggregation level initially, you can improve performance and allow users to expand specific sections of the hierarchy as needed for more detailed analysis.

References:

SAP Analytics Cloud Help Documentation: Improving Story Performance

SAP Analytics Cloud User Guide: Managing Data Hierarchy for Performance

When you have a dimension with members for product groups and associated products and want to plan by product group without disaggregating into the individual products, using two hierarchies is the best approach. One hierarchy can represent the product groups at a higher level, allowing for planning and analysis at the group level. The second hierarchy can include both the product groups and their associated individual products for more detailed analysis when needed. This approach provides flexibility in planning and analyzing data at different levels of detail without the necessity of disaggregating data at the product group level.

References:

SAP Analytics Cloud Help Documentation: Hierarchies in Planning

SAP Analytics Cloud User Guide: Managing Hierarchies for Planning

In the context of creating an allocation step to distribute expenses from the HR cost center to operating cost centers in SAP Analytics Cloud, the "Driver" dimension setting is crucial. This setting determines the basis or criteria on which the distribution is calculated and applied to each operating cost center. For instance, the driver could be the number of employees, square footage, or any other relevant metric that justifies the distribution of costs. By defining a driver, you ensure that the allocation of expenses is proportional and fair based on the selected criteria.

References:

SAP Analytics Cloud Help Documentation: Allocation Steps in Planning

SAP Analytics Cloud User Guide: Using Drivers for Allocation

When inputting new data for a private version in a story in SAP Analytics Cloud, it is necessary to "Publish" the data to ensure it is added to the model. Publishing the private version commits the changes to the underlying model, making the new data visible and accessible to other users according to their permissions. This step is crucial for ensuringthat the updated data is incorporated into the shared model for further analysis and decision-making.

References:

SAP Analytics Cloud Help Documentation: Private Versions and Publishing

SAP Analytics Cloud User Guide: Working with Private Versions in Stories

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 pagetype 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