SAP C_SAC Exam Information and Actual Questions

  • Exam Code/Number: C_SAC
  • Exam Name/Title: SAP Certified - Data Analyst - SAP Analytics Cloud
  • Certification Provider: SAP
  • Corresponding Certification: SAP Certification Exams
  • Exam Questions: 123
  • Updated On: Jul 09, 2026

C_SAC
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SAP
C_SAC Exam
SAP Certified - Data Analyst - SAP Analytics Cloud

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SAP C_SAC Exam Overview:

Certification Vendor:SAP
Exam Name:SAP Certified - Data Analyst - SAP Analytics Cloud
Exam Number:C_SAC (C_SAC_2601 / C_SAC_2501)
Certificate Validity Period:3 years
Exam Duration:120 - 180
Exam Price:200 - 249 USD
Exam Format:Scenario-based assessment, Multiple choice (single/multiple answer), AI-guided roleplay
Available Languages:English, German, French, Spanish, Japanese, Chinese
Passing Score:60% - 70%
Real Exam Qty:10 - 60
Related Certifications:SAP Certified Application Associate - SAP Analytics Cloud
SAP Certified Specialist - SAP Analytics Cloud Planning
Sample Questions:SAP C_SAC Sample Questions
Exam Way:Online remote proctored exam; available 24/7
Pre Condition:No mandatory prerequisites; recommended basic knowledge of data analysis and SAP Analytics Cloud
Official Syllabus URL:https://learning.sap.com/certification/certification/C_SAC

SAP C_SAC Exam Syllabus Topics:

SectionWeightObjectives
Performance and Troubleshooting<= 10%- Optimization and maintenance
  • 1. Common issues and solutions
    • 2. Performance monitoring
      SAP Analytics Cloud Overview and Architecture10% - 15%- Core functionalities and navigation
      • 1. Platform components and workspace
      • 2. Security and access management
      Data Visualization and Story Design25% - 30%- Story building and dashboard creation
      • 1. Widgets, charts, and filters
        • 2. Best practices for design and usability
          Data Modeling25% - 30%- Model design and management
          • 1. Calculations and advanced formulas
            • 2. Dimensions, measures, and hierarchies
              Analytics and Predictive Capabilities10% - 15%- Analysis tools and predictive features
              • 1. Simulation and planning functions
                • 2. Smart insights and forecasting
                  Data Preparation and Connections15% - 20%- Data acquisition and integration
                  • 1. Live and import connections
                    • 2. Data transformation and cleansing


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