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| 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.
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| Topic 2 |
- 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.
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| 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.
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| Topic 4 |
- 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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| Topic 5 |
- 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.
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SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q23-Q28):
NEW QUESTION # 23
What must you use to transform data in a dataset using if/then/else logic?
- A. Custom expression editor
- B. Calculations editor
- C. Formula bar
- D. Transform bar
Answer: A
Explanation:
To transform data in a dataset using if/then/else logic in SAP Analytics Cloud, you must use the Custom expression editor. This tool allows you to write complex logical conditions and perform conditional data transformations. The steps involved are:
Open the dataset you want to transform.
Navigate to the "Custom expression editor".
Write your if/then/else logic using the syntax supported by SAP Analytics Cloud. For example:
IF([Sales] > 1000, "High", "Low")
Apply the expression to the relevant column.
Validate and save your changes.
This approach allows for flexibility and precision in transforming your data based on specific conditions.
Reference:
SAP Help Portal: SAP Analytics Cloud
Official SAP Analytics Cloud Documentation
NEW QUESTION # 24
Which tasks can you perform in data analyzer? Note: There are 2 correct answers to this question.
- A. Drill down on data
- B. Input data
- C. Create cross-calculation
- D. Filter data
Answer: A,D
Explanation:
In Data Analyzer, users can perform various tasks to analyze their data, including filtering data and drilling down on data. Filtering allows users to narrow down the dataset to focus on specific subsets of data, enhancing the analysis's relevancy. Drilling down provides the ability to explore data at a more granular level, revealing deeper insights into the data points and trends within the larger dataset.
Reference:
SAP Analytics Cloud Help Documentation: Data Analyzer Usage
SAP Analytics Cloud User Guide: Filtering and Drilling Down in Data Analyzer
NEW QUESTION # 25
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 # 26
You have a live data model with two dimensions: Firstname and Lastname. Users want a single dimension in the data model that displays the dimensions as Lastname, Firstname. What must you do?
- A. Group the Firstname and Lastname in the data model.
- B. Create a calculated dimension in the data model.
- C. Create a calculated dimension in the story.
- D. Create the combined data in the source system.
Answer: B
Explanation:
To combine two dimensions, Firstname and Lastname, into a single dimension displaying as Lastname, Firstname in a live data model, you should create a calculated dimension in the data model. This calculated dimension will concatenate the two fields into one, according to the specified format. This approach allows for the creation of a new dimension that can be used across various reports and analyses within the model, maintaining the integrity of the original dimensions.
Reference:
SAP Analytics Cloud Help Documentation: Creating Calculated Dimensions
SAP Analytics Cloud User Guide: Data Modeling Best Practices
NEW QUESTION # 27
You are creating a new public version. Which categories can you use? Note: There are 2 correct answers to this question.
- A. Actual
- B. Forecast
- C. Predictive
- D. Budget
Answer: A,D
NEW QUESTION # 28
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