Latest Updated SAP New C_SAC_2501 Exam Test - Certified SAP Certified Associate - Data Analyst - SAP Analytics Cloud Questions

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SAP C_SAC_2501 Exam Syllabus Topics:

Topic	Details
Topic 1	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.
Topic 2	Planning: This section evaluates the expertise of Business Intelligence Developers. The focus is on planning and strategic aspects of data visualization projects.
Topic 3	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 4	Data Modeling, Analysis, and Integration: This section assesses the skills of Data Architects and covers data modeling, analysis, and integration.
Topic 5	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.

SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q49-Q54):

NEW QUESTION # 49
You have a story in My Files. You want your colleague to review and comment on the story. What must you do?

A. Share with View access
B. Add a Comment widget to the story
C. Create a Review task for the story
D. Include the story in a Discussion

Answer: A

NEW QUESTION # 50
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 # 51
You want to display differences between measures in a chart. What can you use?

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

Answer: B

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 # 52
How can you help a user enter data faster in a planning story? Note: There are 2 correct answers to this question.

A. Select fluid data entry mode in the story.
B. Enable Optimize Recommended Planning Area in the model.
C. Set Size Limits for Planning Performance in the model.
D. Enable unbooked data in the story.

Answer: A,B

NEW QUESTION # 53
Your embedded dataset in SAP Analytics Cloud has columns for Country, Region, City, and Customer Name. You want to aggregate measures for these columns as a single column. What can you do?

A. Convert the embedded dataset to a model.
B. Create a level-based hierarchy in the dataset.
C. Create a group that includes the dimensions.
D. Create a parent-child hierarchy in the dataset.

Answer: B

Explanation:
To aggregate measures for columns such as Country, Region, City, and Customer Name as a single column in an embedded dataset, creating a level-based hierarchy is the most effective approach. This type of hierarchy allows you to define a multi-level structure that represents the logical relationship between different geographical entities and customer names. By doing so, you can easily perform aggregations and analyze data at various levels of detail, from the broadest level (e.g., Country) down to the most specific one (e.g., Customer Name).
Reference:
SAP Analytics Cloud Help Documentation: Creating Hierarchies in Models
SAP Analytics Cloud User Guide: Data Modeling and Hierarchies

NEW QUESTION # 54
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