In today’s world, businesses rely heavily on data, so there’s a big need for people who can analyze and understand it well. The SAP Certified Associate – Data Analyst – SAP Analytics Cloud certification (Exam Code: C_SAC_2415) is made to show that someone has the skills needed to work with SAP Analytics Cloud. This certification proves that a person knows how to use SAP Analytics Cloud for analyzing data, creating visuals, and reporting.
About the Certification
The C_SAC_2415 certification is part of SAP’s Certified Associate program. It is designed for people who are new to SAP technologies but have some hands-on experience from training or work. This certification specifically targets the role of a data analyst using SAP Analytics Cloud, which is a strong cloud-based analytics tool.
Exam Details
- Exam Code: C_SAC_2415
- Exam Name: SAP Certified Associate – Data Analyst – SAP Analytics Cloud
- Certification Level: Associate
- Vendor: SAP
Exam Format and Structure
The C_SAC_2415 exam usually has multiple-choice questions that check what you know and how well you can apply that knowledge. The number of questions can change, but you can expect around 60 to 80 questions to be answered in 180 minutes. To pass, you generally need a score of 65% or more.
Key Topics Covered
The exam covers a wide range of topics related to SAP Analytics Cloud. Candidates should be well-versed in the following areas:
- SAP Analytics Cloud Overview
- Understanding the platform’s capabilities and use cases
- Navigating the user interface and key features
- Data Modeling and Preparation
- Creating and managing data models
- Data cleansing and transformation techniques
- Working with different data sources and connectors
- Data Visualization and Storytelling
- Creating various types of charts, graphs, and dashboards
- Designing interactive and compelling data stories
- Applying best practices in data visualization
- Analytics and Reporting
- Performing basic and advanced analytics
- Creating and customizing reports
- Implementing filters, calculations, and formulas
- Collaboration and Sharing
- Sharing analytics content with team members
- Setting up permissions and access controls
- Collaborating on data analysis projects
- SAP Analytics Cloud Administration
- Basic system administration tasks
- Managing users and roles
- Configuring system settings and preferences
Preparation Strategies
To successfully pass the C_SAC_2415 exam, candidates should consider the following preparation strategies:
- Study Materials: Utilize SAP C_SAC_2415 certification guide of DumpsLink online resources.
- Practice Tests: Take practice exams of Dumps Link to familiarize yourself with the question format and identify areas that need improvement.
Benefits of Certification
Obtaining the SAP Certified Associate – Data Analyst – SAP Analytics Cloud certification offers several benefits:
- Career Advancement: Enhance your resume and stand out in the job market as a certified SAP Analytics Cloud professional.
- Skill Validation: Demonstrate your proficiency in using SAP Analytics Cloud for data analysis and visualization.
- Increased Earning Potential: Certified professionals often command higher salaries in the job market.
- Professional Network: Gain access to a community of SAP professionals and potential career opportunities.
- Up-to-date Knowledge: Stay current with the latest features and best practices in SAP Analytics Cloud.
Conclusion
The SAP Certified Associate – Data Analyst – SAP Analytics Cloud (C_SAC_2415) certification is a great opportunity for future data analysts to prove their skills in using SAP’s cloud-based analytics tools. By studying hard for this exam and getting practical experience with SAP Analytics Cloud, candidates can improve their chances of succeeding in the fast-growing field of data analytics and business intelligence.
C_SAC_2415 Sample Exam Questions and Answers
| QUESTION: 1 |
| What must you use to transform data in a dataset using if/then/else logic? Option A: Calculations editor Option B: Custom expression editor Option C: Formula bar Option D: Transform bar |
| Correct Answer: A |
| Explanation/Reference: To transform data in a dataset using if/then/else logic within SAP Analytics Cloud, the Calculations editor is used. This feature allows users to create calculated columns or measures based on conditional logic, enabling complex data manipulation and enhancement directly within the platform. The Calculations editor provides a flexible environment to apply logical expressions, arithmetic operations, and functions to dataset columns, facilitating customized data analysis and reporting needs. |
| QUESTION: 2 |
| Which feature enables you to display details about a data point in a chart? Please choose the correct answer. Option A: Search to Insight Option B: Smart Insights Option C: Smart Discovery Option D: Smart Predict |
| Correct Answer: B |
| QUESTION: 3 |
| Where can you change a data lock status? Note: There are 2 correctanswers to this question. Option A: Data action Option B: Value lock management Option C: Multi action Option D: Calendar task |
| Correct Answer: B,D |
| Explanation/Reference: The data lock status in SAP Analytics Cloud can be changed in the “Value Lock Management” and “Calendar Task” areas. Value Lock Management allows administrators to lock or unlock specific data values to prevent unauthorized or accidental changes, ensuring data integrity. Calendar Tasks, which are part of the collaborative planning features, can also be used to control data lock status as part of workflow management, ensuring that data is only editable during specific periods or under certain conditions, thereby enhancing data governance. References: SAP Analytics Cloud Help Documentation: Managing Data Locks SAP Analytics Cloud User Guide: Calendar Tasks and Data Governance |
| QUESTION: 4 |
| Which automatically created dimension type can you delete from an analytic data model? Option A: Version Option B: Date Option C: Organization Option D: Generic |
| Correct Answer: D |
| Explanation/Reference: 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. References: SAP Analytics Cloud Help Documentation: Data Model Dimensions SAP Analytics Cloud User Guide: Managing Dimensions in Analytic Models |
| QUESTION: 5 |
| Your story takes a long time to open. What could cause this? Note:There are 3 correctanswersto thisquestion. Option A: Large calculation scope Option B: Many story filters Option C: Many hyperlinks Option D: Complex formatting Option E: Many data sources |
| Correct Answer: A,D,E |
| Explanation/Reference: Factors that can cause a story to take a long time to open include a large calculation scope, complex formatting, and the use of many data sources. Extensive calculations and complex formatting can demand significant processing power, while multiple data sources may increase the time required to fetch and consolidate data, all of which can negatively impact the overall performance and loading times of a story. References:SAP Analytics Cloud Help Documentation: Story Performance Considerations SAP Analytics Cloud User Guide: Managing Story Complexity and Data Sources for Better Performance |
| QUESTION: 6 |
| In SAP Analytics Cloud, when does SAP recommend you use a data model instead of a dataset? Option A: To define a dimension Option B: To create ad-hoc analysis Option C: To use a Live connection Option D: To wrangle data |
| Correct Answer: C |
| QUESTION: 7 |
| In which panel can you change the general appearance of a page in a story? Please choose the correct answer. Option A: Visualization Option B: Builder Option C: Styling Option D: Chart |
| Correct Answer: C |
| QUESTION: 8 |
| Which filter type can you select when you enable watch Exporting for PDF files? Please choose the correct answer. Option A: Chart filter Option B: storY filter Option C: Page filter Option D: Measure filter |
| Correct Answer: B |
| QUESTION: 9 |
| You are creating a script for an advanced data action. Which character designates a virtual variable member? Option A: % Option B: / Option C: * Option D: # |
| Correct Answer: D |
| Explanation/Reference: In SAP Analytics Cloud, when creating scripts for advanced data actions, a virtual variable member is designated by the “#” character. Virtual variable members are used within the scripting environment to represent temporary placeholders or variables that can hold values or results during the execution of the script. They are essential for dynamic calculations, conditional logic, and storing interim results that are not part of the permanent data model. References: SAP Analytics Cloud Help Documentation: Advanced Data Actions and Scripting SAP Analytics Cloud User Guide: Scripting and Variables |
| QUESTION: 10 |
| What account types use the average rate type? Note: There are 2 correctanswers to this question. Option A: INC Option B: AST Option C: EXP Option D: LEQ |
| Correct Answer: B,D |
| Explanation/Reference: In SAP Analytics Cloud, the average rate type is typically used with “AST” (Assets) and “LEQ” (Liabilities and Equity) account types. These account types represent balance sheet items, for which averages are often used in financial reporting and analysis,especially for calculating ratios or performance indicators that require average values over a period, such as average assets or average equity. References: SAP Analytics Cloud Help Documentation: Account Types and Rate Types SAP Analytics Cloud User Guide: Financial Planning and Analysis |
| QUESTION: 11 |
| Which tasks can you perform in data analyzer? Note: There are 2 correctanswers to this question. Option A: Input data Option B: Filter data Option C: Drill down on data Option D: Create cross-calculation |
| Correct Answer: B,C |
| Explanation/Reference: 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. References: SAP Analytics Cloud Help Documentation: Data Analyzer Usage SAP Analytics Cloud User Guide: Filtering and Drilling Down in Data Analyzer |
| QUESTION: 12 |
| Which global performance indicators does Smart Predict use? Note: There are 2 correct Answers to this question. Option A: Prediction Confidence Option B: Predictive Power Option C: Prediction Classifications Option D: Predictive Statistics |
| Correct Answer: A,B |
| QUESTION: 13 |
| Which provider offers SAP Analytics Cloud as platform as a service (PaaS)? Please choose the correct answer. Option A: IBM Cloud Solution Option B: Amazon Web Services Option C: Google Web Services Option D: Telekom Web Services |
| Correct Answer: B |
| QUESTION: 14 |
| Your embedded dataset in SAP Analytics Cloud has columns for Country, Region, City, and Customer Name. You want to aggregate measures for these columns as a single column. What can you do? Option A: Create a group that includes the dimensions. Option B: Create a level-based hierarchy in the dataset. Option C: Create a parent-child hierarchy in the dataset. Option D: Convert the embedded dataset to a model. |
| Correct Answer: B |
| Explanation/Reference: To aggregate measures for columns such as Country, Region, City, and Customer Name as a single column in an embedded dataset, creating a level-based hierarchy is the most effective approach. This type of hierarchy allows you to define a multi-level structure that represents the logical relationship between different geographical entities and customer names. By doing so, you can easily perform aggregations and analyze data at various levels of detail, from the broadest level (e.g., Country) down to the most specific one (e.g., Customer Name). References: SAP Analytics Cloud Help Documentation: Creating Hierarchies in Models SAP Analytics Cloud User Guide: Data Modeling and Hierarchies |
| QUESTION: 15 |
| Which collaboration type is supported by SAP Analytics Cloud? There are 3 correct answers to this question. Option A: Discussion Option B: Chat Option C: Calendar Option D: Project groups Option E: Comment |
| Correct Answer: A,C |
| QUESTION: 16 |
| Which live data sources can you use to schedule a story? There are 3 correct answers to this question. Option A: SAP BW Option B: SAP BPC Option C: SAP HANA Option D: SAP HANA Cloud Option E: SAP Data Warehouse Cloud |
| Correct Answer: A,C,D |
| QUESTION: 17 |
| How can you improve the performance of advanced data actions? Note: There are 3 correct answers to this question. Option A: Use fewer MEMBERSET statements Option B: Use fewer FOREACH functions Option C: Use fewer IF statements Option D: Use fewer data functions Option E: Use fewer aggregation dimension functions |
| Correct Answer: A,B,C |
| Explanation/Reference: To improve the performance of advanced data actions in SAP Analytics Cloud, it’s advisable to use fewer MEMBERSET statements, FOREACH functions, and IF statements. MEMBERSET statements can be resource-intensive as they generate sets of members for processing. Minimizing their use can reduce the computational load. Similarly, FOREACH functions, which iterate over sets of members, can significantly impact performance if used extensively. Reducing the number of IF statements can also help, as each condition evaluation adds to the processing time. Streamlining these elements in your scripts can lead to more efficient execution of advanced data actions. References: SAP Analytics Cloud Help Documentation: Optimizing Advanced Data Actions SAP Analytics Cloud User Guide: Best Practices for Script Performance |
| QUESTION: 18 |
| SAP Analytics Cloud represents which SAP software strategy? Please choose the correct answer. Option A: Cloud-only strategy Option B: On premise strategy Option C: Platform strategy Option D: Cloud-first strategy |
| Correct Answer: D |
| QUESTION: 19 |
| You are in the builder pane of a story and you cannot edit a calculated measure. What could be the reason? Note: There are 2 correct Answers to this question Option A: The calculated measure is a cross calculation. Option B: The calculated measure is a model formula. Option C: The calculated measure is a table formula. Option D: The calculated measure is used in several pages. |
| Correct Answer: A,D |
| QUESTION: 20 |
| What can you add to a Data Analyzer Insight? Note: There are 2 correct Answers to this question. Option A: Filters Option B: Table formulas Option C: Advanced filters Option D: Calculated measures |
| Correct Answer: A,D |
| QUESTION: 21 |
| Which of the following products can provide data to SAP Analytics Cloud? Option A: SAP Data Warehouse Cloud Option B: Microsoft Azure Option C: SAP HANA Cloud Option D: SAP Infrastructure Cloud Option E: Oracle Cloud Platform |
| Correct Answer: A,C |
| QUESTION: 22 |
| From where can you schedule a story? Note: There are 2 correct Answers to this question. Option A: Files Option B: Calendar Option C: System Option D: Canvas page |
| Correct Answer: A,D |
Tags: C_SAC_2415