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Free SAP C_SAC_2501 Exam Braindumps (page: 2)

Page 2 of 9
PDF with 60 Questions

What source system can you connect to with a live connection?

  1. SAP ERP Central Component
  2. SAP SuccessFactors
  3. SAP Business ByDesign Analytics
  4. SAP Datasphere

Answer(s): D

Explanation:

SAP Analytics Cloud can establish a live connection with various source systems, including SAP Datasphere. This allows for real-time data access and analysis without the need to replicate data into the cloud, which is beneficial for scenarios where data privacy and security are paramount.


Reference:

SAP Analytics Cloud Connection Guide1
SAC Live and Import Connection Overview2
SAP Analytics Cloud: Expand Live Data Source Options3 Live connection in SAP Analytics Cloud: advantages and challenges4 Explaining Where the Data Comes From - SAP Learning5



You are using a live connection for a model.
Where is the data stored?

  1. Public dataset
  2. SAP Analytics Cloud model
  3. Source system
  4. Embedded data set

Answer(s): C

Explanation:

Connections and data preparation
When using a live connection in SAP Analytics Cloud, the data remains stored in the source system. This means that no data is imported or replicated into SAP Analytics Cloud; instead, it is accessed and analyzed in real-time directly from the source system. This approach ensures that the most current data is always used for analysis and that data governance and security policies of the source system remain in control.


Reference:

Live Data Connections to SAP S/4HANA | SAP Help Portal1 SAP Analytics Cloud Connection Guide2
SAP Analytics Cloud Data Connections - InsightCubes
In the context of SAP Analytics Cloud, when using a live connection to connect to a data source, the data remains stored in the source system. This setup means that SAP Analytics Cloud directly queries the data in its original location, without importing or copying it into the SAP Analytics Cloud environment. This approach is advantageous for several reasons, including maintaining a single source of truth, reducing data redundancy, and ensuring data is always up-to-date without the need for synchronization processes. Live connections are particularly useful for real-time or near-real-time data analysis and reporting, providing insights based on the most current data available without the overhead of data replication.


SAP Analytics Cloud documentation and user guides typically emphasize the benefits and use cases of live connections, highlighting how they maintain data in the source system to ensure real-time data access and analysis.
SAP training materials for Data Analysts using SAP Analytics Cloud, including study guides and official certification resources, explain the technical and practical aspects of live connections, including where data is stored and how it is accessed.
Best practice guides for SAP Analytics Cloud, often available through the SAP Community or SAP Knowledge Base, provide insights and recommendations on setting up and using live connections, reinforcing the concept that data stays in the source system.



You are using a live connection for a model.
Where can you define data security?

  1. Source system
  2. Data access control
  3. SAP Analytics Cloud model
  4. SAP Analytics Cloud role

Answer(s): A

Explanation:

When using a live connection in SAP Analytics Cloud, data security is defined and managed within the source system. This approach leverages the existing security protocols and permissions set up in the source system, ensuring that data governance and access controls remain consistent and are centrally managed. Users accessing data through SAP Analytics Cloud with a live connection will be subject to the same security constraints and permissions as if they were accessing the data directly from the source system. This integration ensures a unified security model, simplifying administration and ensuring data security and compliance.



What must you use to transform data in a dataset using if/then/else logic?

  1. Calculations editor
  2. Custom expression editor
  3. Formula bar
  4. Transform bar

Answer(s): B

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.



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?

  1. Change the Year measure to a dimension in the dataset.
  2. Includes the Year measure in a level-based time hierarchy in the dataset.
  3. Insert a character into the Year measure using the transform bar.
  4. Add the month as a suffix to the Year measure.

Answer(s): 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.



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.

  1. Allow model import
  2. Refresh the story
  3. Refresh the import job
  4. Schedule the import

Answer(s): B,D

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.



You need to delete characters from a column in a dataset.
What can you use?
Note: There are 2 correct answers to this question.

  1. Custom expression editor
  2. Formula bar
  3. Calculation editor
  4. Transform bar

Answer(s): A,D



What can you use to organize dimensions into logical categories in a live model?

  1. Level-based hierarchy
  2. Groups
  3. Value driver tree
  4. Parent-child hierarchy

Answer(s): D

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






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