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

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 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

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

In an analytic data model within SAP Analytics Cloud, the automatically created dimension type that you can delete is the Generic dimension. This type of dimension is typically used for custom or ad-hoc categorizations and, unlike system-generateddimensions like Date or Version, can be modified or removed as per the specific needs of your data model and analysis requirements.

References:

SAP Analytics Cloud Help Documentation: Data Model Dimensions

SAP Analytics Cloud User Guide: Managing Dimensions in Analytic Models

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

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.

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 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