C_SAC_2421 VALID TEST TESTKING, C_SAC_2421 LATEST DUMPS BOOK

C_SAC_2421 Valid Test Testking, C_SAC_2421 Latest Dumps Book

C_SAC_2421 Valid Test Testking, C_SAC_2421 Latest Dumps Book

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Free PDF Quiz 2025 High Hit-Rate SAP C_SAC_2421: SAP Certified Associate - Data Analyst - SAP Analytics Cloud Valid Test Testking

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SAP C_SAC_2421 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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.
Topic 4
  • 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 5
  • 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.

SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q43-Q48):

NEW QUESTION # 43
You are using a live connection for a model. Where is the data stored?

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

Answer: C

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 # 44
Your users need to analyze data in a story. What kinds of data models can you create? Note: There are 2 correct answers to this question.

  • A. Standalone
  • B. Analytic
  • C. Embedded
  • D. Planning

Answer: B,D


NEW QUESTION # 45
In a data model, what can you use to further describe a dimension?

  • A. Variable
  • B. Property
  • C. Measure
  • D. Data action

Answer: B

Explanation:
In a data model within SAP Analytics Cloud, Properties are used to further describe dimensions. Properties provide additional context or metadata for dimension members, such as descriptions, classifications, or other attributes that help to better understand and analyze the data within the dimension. This makes properties essential for detailed data analysis and reporting.
Reference:
SAP Analytics Cloud Help Documentation: Dimension Properties
SAP Analytics Cloud User Guide: Enhancing Dimensions with Properties


NEW QUESTION # 46
What type of predictive scenario can write back to a planning model?

  • A. Time series forecast
  • B. Classification
  • C. Value driver tree
  • D. Regression

Answer: A

Explanation:
In SAP Analytics Cloud, a Time Series Forecast predictive scenario can write back to a planning model. Time Series Forecasting leverages historical data to predict future values over a specified time horizon, using statistical or machine learning methods. This feature is particularly useful in planning and forecasting processes, where future values are predicted based on past trends and seasonality. The ability to write these forecasts back into a planning model allows for the integration of predictive insights into the planning process, enhancing decision-making and strategic planning.
Reference:
SAP Analytics Cloud Help Documentation: Predictive Scenarios and Planning SAP Analytics Cloud User Guide: Time Series Forecasting in Planning Models


NEW QUESTION # 47
What can you use to organize dimensions into logical categories in a live model?

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

Answer: A

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 # 48
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