Exam: C_SAC_2421
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EXAM C_SAC_2421
60 questions (2 hrs)
70% cut score
Available in English
Validate your SAP skills and expertise
This certification verifies that you possess the fundamental and core
knowledge required for the SAP Analytics Cloud Data Analyst profile. It proves
that the candidate has an overall understanding and technical skills to
participate as a member of the project team. The beginner Learning Journey
Exploring SAP Analytics Cloud builds up the basic knowledge of SAP Analytics
Cloud and is relevant for passing the certification.
Note: To prepare for this certification, it is necessary to take the Learning
Journey Exploring SAP Analytics Cloud, in addition to the Learning Journey
displayed under "How to Prepare.”
Stay certified and stay ahead
Continuous learning and keeping your skills up to date is a priority and SAP
Certification makes it easy for you to maintain your SAP skills and valid
credentials.
The standard validity of your certification is 12 months.
Every time you successfully complete an assessment, the validity period is
extended by 12 more months.
You’ll receive personalized communication to ensure that you don’t miss your
certification expiry date.
Topic areas
Please see below the list of topics that may be covered within this SAP
Certification and the courses that touches on these topics. Its accuracy does
not constitute a legitimate claim. SAP reserves the right to update the exam
content (topics, items, weighting) at any time.
Story Design
Exam percentage: 21% - 30%
Related course code: SACS21, SACE11
Planning
Exam percentage: 21% - 30%
Related course code: SACP21
Data modeling, analysis, and integration
Exam percentage: 21% - 30%
Related course code: SACE11, SACP21
Connections and data preparation
Exam percentage: 11% - 20%
Related course code: SACS21, SACE11
Performance, troubleshooting, and security management
Exam percentage: ≤10%
Related course code: SACE11, SACS21, SACP21
The SAP Certified Associate - Data Analyst - SAP Analytics Cloud (C_SAC_2421)
exam evaluates your proficiency in various aspects of SAP Analytics Cloud. The
exam encompasses the following key topics, each contributing to a specific
percentage of the total content:
1.Story Design (21% - 30%):
This area assesses your ability to design and present stories within SAP
Analytics Cloud. It includes configuring story elements such as pages, tables,
charts, and other widgets, as well as formatting, filtering, and manipulating
data to create effective visualizations.
2.Planning (21% - 30%):
This section evaluates your understanding of enterprise planning features in
SAP Analytics Cloud. It covers working with planning models and stories,
configuring data actions, managing versions, and utilizing forecasting and
simulation tools to support business planning processes.
3.Data Modeling, Analysis, and Integration (21% - 30%):
This topic focuses on creating and configuring models in SAP Analytics
Cloud, understanding the role and features of the Data Analyzer, and integrating
SAP Analytics Cloud with external applications. Proficiency in these areas
enables effective data analysis and integration across platforms.
4.Connections and Data Preparation (11% - 20%):
This domain covers establishing connections to various data sources,
including on-premise and cloud-based systems, and preparing data for analysis.
It involves identifying appropriate connection types, differentiating among
types of models and datasets, and ensuring data is properly formatted for
analytical tasks.
5.Performance, Troubleshooting, and Security Management (≤10%):
This section addresses maintaining and optimizing SAP Analytics Cloud
environments. It includes identifying performance bottlenecks and their
remedies, understanding the security model within SAP Analytics Cloud, and
implementing security measures to protect data integrity and user access.
A comprehensive understanding of these topics is essential for success in the
C_SAC_2421 exam and for effectively utilizing SAP Analytics Cloud in
professional settings.
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QUESTION 1
What source system can you connect to with a live connection?
A. SAP ERP Central Component
B. SAP SuccessFactors
C. SAP Business ByDesign Analytics
D. SAP Datasphere
Answer: D
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
QUESTION 2
You are using a live connection for a model. Where is the data stored?
A. Public dataset
B. SAP Analytics Cloud model
C. Source system
D. Embedded data set
Answer: C
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 SHANA | 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.
Reference:
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.
QUESTION 3
You are using a live connection for a model. Where can you define data security?
A. Source system
B. Data access control
C. SAP Analytics Cloud model
D. SAP Analytics Cloud role
Answer: A
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.
QUESTION 4
What must you use to transform data in a dataset using if/then/else logic?
A. Calculations editor
B. Custom expression editor
C. Formula bar
D. Transform bar
Answer: B
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
QUESTION 5
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. Includes the Year measure in a level-based time hierarchy in the dataset.
C. Insert a character into the Year measure using the transform bar.
D. Add the month as a suffix to the Year measure.
Answer: A
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.
QUESTION 6
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. Allow model import
B. Refresh the story
C. Refresh the import job
D. Schedule the import
Answer: B D
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.
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Students Feedback / Reviews/ Discussion
Mahrous Mostafa Adel Amin 1 week, 2 days ago - Abuhib- United Arab
Emirates
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upvoted 4 times
Mbongiseni Dlongolo - South Africa2 weeks, 5 days ago
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upvoted 2 times
Kenyon Stefanie 1 month, 1 week ago - USA State / Province = Virginia
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of questions were from here.
upvoted 2 times
Danny 1 month, 1 week ago - United States CUSTOMER_STATE_NAME: Costa Mesa =
USA
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weren’t from exam topics. Rest of them was exactly the same!
MENESES RAUL 93% 2 week ago - USA = Texas
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