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Updated: Jul 18, 2026

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Alibaba Cloud ACE-BigData1 Exam Overview:

Certification Vendor:Alibaba Cloud
Exam Name:Alibaba Cloud ACE Big Data Expert Certification Exam
Exam Number:ACE-BigData1
Related Certifications:Alibaba Cloud Certified Associate (ACA) Big Data
Alibaba Cloud Certified Professional (ACP) Big Data
Exam Price:USD 120
Real Exam Qty:60
Exam Duration:150 minutes
Certificate Validity Period:2 years
Passing Score:90/150
Exam Format:Multiple Choice Questions, Single Choice Questions
Available Languages:English
Recommended Training:Alibaba Cloud Academy Big Data Training
Exam Registration:Alibaba Cloud Certification Portal
Pearson VUE Scheduling
Exam Way:Test center (Pearson VUE) or authorized online proctoring depending on region availability
Pre Condition:Recommended prior experience with Alibaba Cloud Big Data services and completion of ACA and ACP Big Data certifications.
Official Syllabus URL:https://www.alibabacloud.com/en/academy/certification

Alibaba Cloud ACE-BigData1 Exam Syllabus Topics:

SectionObjectives
Big Data Operations and Security- System Operations
  • 1. Cluster monitoring and troubleshooting
    • 2. Resource management and optimization
      - Security and Governance
      • 1. Data access control (RAM)
        • 2. Data compliance and governance
          Data Visualization and BI- Business Intelligence Tools
          • 1. DataV visualization dashboards
            • 2. Quick BI usage scenarios
              Big Data Architecture on Alibaba Cloud- Alibaba Cloud Big Data Ecosystem
              • 1. MaxCompute usage and architecture
                • 2. E-MapReduce cluster management
                  • 3. DataWorks data integration workflows
                    - Core Big Data Concepts
                    • 1. Data storage and processing models
                      • 2. Distributed systems fundamentals
                        Data Processing and Analytics- Data Modeling and Optimization
                        • 1. Dimensional modeling (OLAP/OLTP)
                          • 2. Performance tuning for big data workloads
                            - Batch and Stream Processing
                            • 1. Offline data warehouse design
                              • 2. Real-time data processing concepts

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