SAP C_SAC_2501 SAP Certified Associate - Data Analyst - SAP Analytics Cloud Exam Practice Test

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.

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 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

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.

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.

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.

Input controls in a story in SAP Analytics Cloud can be used for changing dimensions or measures displayed in a table and for filtering data on a page. Input controls provide a way for users to interactively modify the view of the data, such as selecting which dimensions or measures to display, or filtering the entire page's content based on selected criteria, enhancing the interactivity and flexibility of data analysis within stories.

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.

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 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.

In SAP Analytics Cloud, the Account dimension can be used similarly to a measure. This dimension is specifically designed for financial data and can hold various types of financial metrics, such as revenues, expenses, assets, and liabilities. It allows for the application of financial calculations and aggregations, which is why it can function similarly to measures in the context of financial reporting and analysis.