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SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q60-Q65):

NEW QUESTION # 60
Which automatically created dimension type can you delete from an analytic data model?

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

Answer: B

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 # 61
What features are supported by data analyzer? Note: There are 3 correct answers to this question.

A. Linked dimensions
B. Charts
C. Calculated measures
D. Conditional formatting
E. Input controls

Answer: B,C,D

NEW QUESTION # 62
You are creating a data action to copy data from one year to the next.In the parameter for the source year, which default setting must you change?

A. Hierarchy
B. Granularity
C. Level
D. Cardinality

Answer: D

NEW QUESTION # 63
You want to total several income and expense accounts using the account type property.
What configuration option in the advanced formula must you use?

A. Append
B. Aggregate To
C. Unbooked
D. Signflip

Answer: D

NEW QUESTION # 64
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. Create a group that includes the dimensions.
B. Convert the embedded dataset to a model.
C. Create a parent-child hierarchy in the dataset.
D. Create a level-based hierarchy in the dataset.

Answer: D

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 # 65
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