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

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.

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 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 a live model within SAP Analytics Cloud, dimensions can be organized into logical categories using either level-based hierarchies or parent-child hierarchies. Level-based hierarchies are used when the relationships between items are defined by distinct levels, such as Geography might be divided into Country, State, and City levels. Parent-child hierarchies, on the other hand, are useful when the data's hierarchy is not strictly defined by levels but by a parent relationship where a child member is associated with a parent member, which is common in organizational structures or product categories.

References:

SAP Analytics Cloud Help Documentation: Creating and Managing Hierarchies

SAP Analytics Cloud User Guide: Working with Models

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

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

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

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 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

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.

To ensure that labels are always visible on a column chart in a story, you should select the "Avoid Data Label Overlap" checkbox in the chart's settings. This option adjusts the labels' positioning to prevent overlap, making them visible at all times without the need for mouse-over interaction.

References:

SAP Analytics Cloud Help Documentation: Chart Design and Label Management

SAP Analytics Cloud User Guide: Enhancing Data Label Visibility in Charts