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SAP C-SAC-2501 Exam Syllabus Topics:

Topic
Details

Topic 1

Story Design: This section of the exam measures the skills of Data Analysts and covers story design concepts, accounting for The focus on creating effective visualizations and narratives using data.

Topic 2

Connections and Data Preparation: This section targets Data Engineers and covers connections and data preparation, The focus is on connecting to data sources and preparing data for visualization.

Topic 3

Planning: This section evaluates the expertise of Business Intelligence Developers. The focus is on planning and strategic aspects of data visualization projects.

Topic 4

Data Modeling, Analysis, and Integration: This section assesses the skills of Data Architects and covers data modeling, analysis, and integration.

Topic 5

Performance, Troubleshooting, and Security Management: This section measures the skills of IT Administrators and covers performance, troubleshooting, and security management, making up less than 10% of the exam. It focuses on optimizing performance, resolving issues, and ensuring data security in data visualization environments.

SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q29-Q34):

NEW QUESTION # 29
You are using a live connection for a model. Where is the data stored?

A. Source system
B. Embedded data set
C. Public dataset
D. SAP Analytics Cloud model

Answer: A

Explanation:
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.
Reference:
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.
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.

NEW QUESTION # 30
Which automatically created dimension type can you delete from an analytic data model?

A. Date
B. Version
C. Organization
D. Generic

Answer: D

Explanation:
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.
Reference:
SAP Analytics Cloud Help Documentation: Data Model Dimensions
SAP Analytics Cloud User Guide: Managing Dimensions in Analytic Models

NEW QUESTION # 31
You are creating an allocation step to distribute expenses from the HR cost center to your operating cost centers. Which dimension setting controls how much is distributed to each operating cost center?

A. Redistribute
B. Reference
C. Driver
D. Distribute

Answer: C

Explanation:
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.
Reference:
SAP Analytics Cloud Help Documentation: Allocation Steps in Planning
SAP Analytics Cloud User Guide: Using Drivers for Allocation

NEW QUESTION # 32
How can you improve the performance of advanced data actions? Note: There are 3 correct answers to this question.

A. Use fewer aggregation dimension functions
B. Use fewer IF statements
C. Use fewer data functions
D. Use fewer MEMBERSET statements
E. Use fewer FOREACH functions

Answer: B,C,E

NEW QUESTION # 33
What can you use to organize dimensions into logical categories in a live model?

A. Value driver tree
B. Parent-child hierarchy
C. Groups
D. Level-based hierarchy

Answer: B

Explanation:
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.
Reference:
SAP Analytics Cloud Help Documentation: Creating and Managing Hierarchies SAP Analytics Cloud User Guide: Working with Models

NEW QUESTION # 34
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