When creating a styling rule for a table in SAP Analytics Cloud, the context refers to "The most granular level in the table." This means that the styling rule will be applied to the lowest level of data detail available in the table, such as individual cells or rows, allowing for precise control over the appearance of specific data points or categories within the table.
References:
SAP Analytics Cloud Help Documentation: Styling Tables
SAP Analytics Cloud User Guide: Applying Styling Rules to Table Data
Question 2
Which dimension type can you use like a measure?
Options:
A.
Account
B.
Date
C.
Organization
D.
Entity
Answer:
A
Explanation:
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.
References:
SAP Analytics Cloud Help Documentation: Understanding Dimensions and Measures
SAP Analytics Cloud User Guide: Working with Account Dimensions
Question 3
What must a data model contain in SAP Analytics Cloud? Note: There are 2 correctanswersto
thisquestion.
Options:
A.
Calculations
B.
Dimensions
C.
Measures
D.
Hierarchies
Answer:
B, C
Explanation:
Explanation:
In SAP Analytics Cloud, a data model must contain at least "Dimensions" and "Measures" to be functional. Dimensions are the qualitative aspects of the data (e.g., time, geography, product categories) that provide the context for analysis. Measures, on the other hand, are the quantitative data points (e.g., sales, costs, quantities) that are analyzed within the context provided by dimensions. Both are fundamental components of a data model, enabling structured data analysis and reporting.
References:
SAP Analytics Cloud Help Documentation: Building Data Models
SAP Analytics Cloud User Guide: Understanding Dimensions and Measures in Models