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SAP C_SAC_2421 Exam Syllabus Topics:

Topic	Details
Topic 1	Planning: SAP Analytics Cloud Data Analysts are expected to demonstrate proficiency in planning within the SAP Analytics Cloud environment. The exam evaluates the ability to create and manage planning models, including setting up dimensions, accounts, and versions. Candidates should be familiar with creating planning input forms and implementing planning processes.
Topic 2	Performance, troubleshooting, and security management: This domain covers critical aspects of maintaining and optimizing SAP Analytics Cloud environments. It assesses SAP Analytics Cloud Data Analysts' abilities in performance tuning, troubleshooting common issues, and implementing security measures.
Topic 3	Data modeling, analysis, and integration: This section focuses on the core analytical capabilities of SAP Analytics Cloud. SAP Analytics Cloud Data Analysts should demonstrate proficiency in creating and managing data models, performing advanced analysis, and integrating data from various sources. The exam assesses skills in creating calculated measures, applying filters, and using advanced analytical functions.
Topic 4	Story Design: This section of the exam measures the skills of SAP Analytics Cloud Data Analysts and covers various aspects of story design in SAP Analytics Cloud. The exam assesses the knowledge of candidates who should be able to create effective and visually appealing stories to present data insights. This includes understanding different chart types, layout options, and interactive elements to enhance data visualization and user engagement.
Topic 5	Connections and data preparation: This domain covers the essential skills of connecting to data sources and preparing data for analysis. SAP Analytics Cloud Data Analysts are expected to show competence in establishing connections to various data sources, including on-premise and cloud-based systems.

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SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q44-Q49):

NEW QUESTION # 44
What can you use to organize dimensions into logical categories in a live model?

A. Groups
B. Parent-child hierarchy
C. Value driver tree
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 # 45
Which tasks can you perform in data analyzer? Note: There are 2 correct answers to this question.

A. Drill down on data
B. Input data
C. Create cross-calculation
D. Filter data

Answer: A,D

Explanation:
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.
Reference:
SAP Analytics Cloud Help Documentation: Data Analyzer Usage
SAP Analytics Cloud User Guide: Filtering and Drilling Down in Data Analyzer

NEW QUESTION # 46
You are using a live connection for a model. Where is the data stored?

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

Answer: D

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 # 47
You want to display differences between measures in a chart. What can you use?

A. Variance
B. Restricted measure
C. Threshold
D. Reference line

Answer: A

Explanation:
To display differences between measures in a chart within SAP Analytics Cloud, you can use the Variance feature. Variance helps to highlight the differences or gaps between two data points or measures, making it easier to identify trends, outliers, or areas requiring attention in visual representations like charts.
Reference:
SAP Analytics Cloud Help Documentation: Variance Analysis in Charts
SAP Analytics Cloud User Guide: Displaying Measure Differences Using Variance

NEW QUESTION # 48
You import data into a dataset. One of the columns imported is Year, and SAP Analytics Cloud interprets it as a measure. How can you ensure that it is treated as a calendar year?

A. Includes the Year measure in a level-based time hierarchy in the dataset.
B. Change the Year measure to a dimension in the dataset.
C. Insert a character into the Year measure using the transform bar.
D. Add the month as a suffix to the Year measure.

Answer: B

Explanation:
If SAP Analytics Cloud interprets a 'Year' column as a measure instead of a dimension, it should be changed to a dimension to ensure it is treated as a calendar year. This adjustment can be made within the model or dataset settings, where the column's role can be switched from a measure (quantitative value) to a dimension (qualitative value). Treating 'Year' as a dimension allows it to be used appropriately in time-based analyses, such as trends over time, without being aggregated like a numerical measure.

NEW QUESTION # 49
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