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SAP C-SAC-2421 Exam Syllabus Topics:

Topic
Details

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

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.

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

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 5

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.

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SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q55-Q60):

NEW QUESTION # 55
You have a story based on an import model. The transaction data in the model's data source changes. How can you update the data in the model? Note: There are 2 correct answers to this question.

A. Refresh the story
B. Allow model import
C. Schedule the import
D. Refresh the import job

Answer: A,C

Explanation:
To update the data in a model based on an import connection, two main approaches can be used:
Refresh the story: This action forces SAP Analytics Cloud to reload the data for the visualizations in a story, pulling in the most recent data available in the model. This is a manual process initiated by the user.
Schedule the import: This option allows users to set up a recurring data import schedule, ensuring the model is regularly updated with the latest data from the source system. This automated process helps maintain data freshness without manual intervention.
Both methods ensure that the story reflects the most current data, accommodating changes in the transaction data of the model's data source.

NEW QUESTION # 56
What can you use to organize dimensions into logical categories in a live model?

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

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 # 57
Which automatically created dimension type can you delete from an analytic data model?

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

Answer: A

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 # 58
You have a dataset that extracts data from an SAP Business Warehouse (SAP BW) system. The data in the SAP BW system changes. How can you update the dataset?

A. You must refresh the story that uses the dataset.
B. You must manually reimport the data.
C. You can schedule the dataset to update on a regular basis.
D. You must create a new dataset.

Answer: C

Explanation:
For datasets that extract data from external systems like SAP Business Warehouse (SAP BW), SAP Analytics Cloud provides the capability to schedule updates on a regular basis. This feature ensures that the dataset within SAP Analytics Cloud remains up-to-date with the latest changes from the SAP BW system, without the need for manual reimport or creating a new dataset. Scheduled updates can be configured to run at specific intervals, automating the data refresh process.
Reference:
SAP Analytics Cloud Help Documentation: Scheduling Data Refresh
SAP Analytics Cloud User Guide: Automating Dataset Updates from External Sources

NEW QUESTION # 59
You are entering values for several expense accounts in a data table. Which data entry mode must you use to process the data with a delay defined in System Administration?

A. Fluid
B. Mass
C. Single

Answer: A

NEW QUESTION # 60
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