SAP C_SAC_2415 SAP Certified Associate - Data Analyst - SAP Analytics Cloud Exam Practice Test

Version management in SAP Analytics Cloud stories requires a Planning model. This feature enables users to create and manage different versions of their data, such as budget, forecast, and actual versions. Planning models provide the necessary structure and functionality for versioning, allowing for comparisons and what-if analyses within the story.

References:

SAP Analytics Cloud Help Documentation: Version Management in Planning

SAP Analytics Cloud User Guide: Using Planning Models for Versioning

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

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

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

SAP Analytics Cloud can establish a live connection with various source systems, including SAP Datasphere. This allows for real-time data access and analysis without the need to replicate data into the cloud, which is beneficial for scenarios where data privacy and security are paramount.

References:

SAP Analytics Cloud Connection Guide1

SAC Live and Import Connection Overview2

SAP Analytics Cloud: Expand Live Data Source Options3

Live connection in SAP Analytics Cloud: advantages and challenges4

Explaining Where the Data Comes From - SAP Learning5

In a data model within SAP Analytics Cloud, Properties are used to further describe dimensions. Properties provide additional context or metadata for dimension members, such as descriptions, classifications, or other attributes that help to better understand and analyze the data within the dimension. This makes properties essential for detailed data analysis and reporting.

References:

SAP Analytics Cloud Help Documentation: Dimension Properties

SAP Analytics Cloud User Guide: Enhancing Dimensions with Properties

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

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

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

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