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.

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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.

For a more in-depth understanding and preparation, you might find the following video resource helpful:

Sample Question and Answers

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.