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SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q28-Q33):
NEW QUESTION # 28
What type of predictive scenario can write back to a planning model?
- A. Time series forecast
- B. Regression
- C. Value driver tree
- D. Classification
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 # 29
Which dimension type can you use like a measure?
- A. Date
- B. Entity
- C. Account
- D. Organization
Answer: C
Explanation:
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.
Reference:
SAP Analytics Cloud Help Documentation: Understanding Dimensions and Measures SAP Analytics Cloud User Guide: Working with Account Dimensions
NEW QUESTION # 30
What can you use to organize dimensions into logical categories in a live model?
- A. Groups
- B. Level-based hierarchy
- C. Parent-child hierarchy
- D. Value driver tree
Answer: C
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 # 31
How can you limit the refresh time of a story?
- A. Collapse the hierarchy
- B. Implement a value driver tree
- C. Use canvas pages
- D. Create calculated measures
Answer: A
Explanation:
Collapsing the hierarchy in a story can help limit the refresh time, as it reduces the amount of data that needs to be processed and displayed at any given time. By presenting data at a higher aggregation level initially, you can improve performance and allow users to expand specific sections of the hierarchy as needed for more detailed analysis.
Reference:
SAP Analytics Cloud Help Documentation: Improving Story Performance
SAP Analytics Cloud User Guide: Managing Data Hierarchy for Performance
NEW QUESTION # 32
What are the available connection types in SAP Analytics Cloud? Note: There are 2 correct answers to this question.
- A. On-premise
- B. Cloud
- C. Import
- D. Live
Answer: C,D
Explanation:
SAP Analytics Cloud supports two primary types of data connections: Live Data Connection and Import Data Connection. Live Data Connection establishes a direct link to the data source, allowing real-time data access without replicating the data into SAP Analytics Cloud. This is ideal for scenarios where up-to-the-minute data is crucial, and data volume is large. On the other hand, Import Data Connection involves copying data from the source into SAP Analytics Cloud, which is suitable for scenarios where data doesn't change frequently, or there's a need for data transformation and enrichment within SAP Analytics Cloud.
Reference:
SAP Analytics Cloud Help Documentation: Data Connections Overview
SAP Analytics Cloud User Guide: Live Data vs. Import Data Scenarios
NEW QUESTION # 33
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