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SAP C_SAC_2421 exam prep, pass C_SAC_2421 exam

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SAP C_SAC_2421 Exam Syllabus Topics:

Topic
Details

Topic 1

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.

Topic 2

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 3

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 4

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 5

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.

SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q19-Q24):

NEW QUESTION # 19
Which automatically created dimension type can you delete from an analytic data model?

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

Answer: D

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 # 20
What are the available connection types in SAP Analytics Cloud? Note: There are 2 correct answers to this question.

A. Live
B. Import
C. On-premise
D. Cloud

Answer: A,B

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 # 21
Your users need to analyze data in a story. What kinds of data models can you create? Note: There are 2 correct answers to this question.

A. Planning
B. Embedded
C. Analytic
D. Standalone

Answer: A,C

NEW QUESTION # 22
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 # 23
You import data into a dataset. One of the columns imported is Year, and SAP Analytics Cloud interprets it as a measure. How can you ensure that it is treated as a calendar year?

A. Change the Year measure to a dimension in the dataset.
B. Insert a character into the Year measure using the transform bar.
C. Includes the Year measure in a level-based time hierarchy in the dataset.
D. Add the month as a suffix to the Year measure.

Answer: A

Explanation:
If SAP Analytics Cloud interprets a 'Year' column as a measure instead of a dimension, it should be changed to a dimension to ensure it is treated as a calendar year. This adjustment can be made within the model or dataset settings, where the column's role can be switched from a measure (quantitative value) to a dimension (qualitative value). Treating 'Year' as a dimension allows it to be used appropriately in time-based analyses, such as trends over time, without being aggregated like a numerical measure.

NEW QUESTION # 24
......

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