C_SAC_2501 SAP Certified Associate - Data Analyst - SAP Analytics Cloud Questions and Answers

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.

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.

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.

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.

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.

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.

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-generated dimensions like Date or Version, can be modified or removed as per the specific needs of your data model and analysis requirements.

To combine two dimensions, Firstname and Lastname, into a single dimension displaying as Lastname, Firstname in a live data model, you should create a calculated dimension in the data model. This calculated dimension will concatenate the two fields into one, according to the specified format. This approach allows for the creation of a new dimension that can be used across various reports and analyses within the model, maintaining the integrity of the original dimensions.

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.

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.

To transform data in a dataset using if/then/else logic in SAP Analytics Cloud, you must use the Custom expression editor. This tool allows you to write complex logical conditions and perform conditional data transformations. The steps involved are:

Open the dataset you want to transform.

Navigate to the "Custom expression editor".

Write your if/then/else logic using the syntax supported by SAP Analytics Cloud. For example:

IF([Sales] > 1000, "High", "Low")

Apply the expression to the relevant column.

Validate and save your changes.

This approach allows for flexibility and precision in transforming your data based on specific conditions.

References :=

SAP Help Portal: SAP Analytics Cloud

Official SAP Analytics Cloud Documentation