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Alibaba Data-ACA Exam Overview:

Certification Vendor:Alibaba Cloud
Exam Name:Alibaba Cloud Certified Data Engineer (Associate)
Exam Number:Data-ACA
Passing Score:80/100
Certificate Validity Period:2 years from the date the certificate is claimed
Exam Price:USD 200
Real Exam Qty:50
Related Certifications:Alibaba Cloud Certified Data Engineer (Associate)
Available Languages:English
Exam Format:Multiple-choice, Single-choice
Exam Duration:60 minutes
Exam Way:Online or onsite testing options are presented on the official exam page. Alibaba Cloud's certification guidance identifies ACA exams as available online through the official certification platform. Confirm the currently available delivery options during registration.
Pre Condition:No mandatory prerequisite exam, age, education, major, or work-experience requirement is specified. A basic understanding of cloud computing concepts is recommended. Intended for entry-level data professionals, analysts, IT operations staff, technical managers, and students.
Official Syllabus URL:https://www.alibabacloud.com/en/academy/certification_data_engineer_associate?_p_lc=1

Alibaba Data-ACA Exam Syllabus Topics:

SectionWeightObjectives
Data Integration, Storage, and Processing30%- Data Integration and Transmission
  • 1. Batch and real-time data synchronization
    • 2. Full and incremental data synchronization
      • 3. Message queues and Kafka data buffering
        • 4. Zero-ETL architecture and use cases
          • 5. Full-database synchronization and DDL change detection
            • 6. DataWorks Data Integration, DTS, Flink CDC, and ApsaraMQ for Kafka
              • 7. Change Data Capture and database binary logs
                - Data Processing and Transformation
                • 1. ETL and ELT concepts
                  • 2. MaxCompute and EMR Serverless Spark
                    • 3. Realtime Compute for Apache Flink
                      • 4. Selecting processing engines based on latency and workload requirements
                        • 5. SQL queries, filtering, grouping, sorting, joins, and aggregate functions
                          • 6. Flink tumbling, sliding, and session windows and complex event processing
                            • 7. Lambda architecture, Kappa architecture, and unified stream and batch processing
                              • 8. MapReduce and Spark processing architectures
                                • 9. Apache Flink stateful computation, checkpoints, and exactly-once semantics
                                  • 10. Hologres interactive analytics
                                    • 11. Batch processing, stream processing, and interactive analytics
                                      - Data Storage and Management
                                      • 1. Data Lake Formation metadata management
                                        • 2. Lindorm wide-table engine and use cases
                                          • 3. Apache Paimon and Apache Iceberg lake table formats
                                            • 4. MaxCompute columnar storage and batch analytics
                                              • 5. ACID transactions, Time Travel, and schema evolution
                                                • 6. Structured, semi-structured, and unstructured data
                                                  • 7. Row-oriented and column-oriented storage
                                                    • 8. Lakehouse architecture and small-file optimization
                                                      • 9. Hot and cold data tiering between MaxCompute and Hologres
                                                        • 10. Object Storage Service storage and use cases
                                                          • 11. Hologres hybrid row-column storage and interactive queries
                                                            - Data Lifecycle Management
                                                            • 1. Object Storage Service storage classes and restoration
                                                              • 2. Object Storage Service versioning, lake table Time Travel, and cross-region replication
                                                                • 3. Hot, warm, and cold data tiering
                                                                  • 4. Automated lifecycle rules and data expiration
                                                                    • 5. Backup and disaster recovery strategies
                                                                      • 6. MaxCompute tiered storage
                                                                        • 7. Data retention policies and compliance requirements
                                                                          Data Governance and Security25%- Data Quality and Observability
                                                                          • 1. Root-cause analysis and downstream impact assessment
                                                                            • 2. Data quality dimensions: completeness, accuracy, consistency, timeliness, uniqueness, and validity
                                                                              • 3. Critical path identification and Operation Center O&M Dashboard
                                                                                • 4. Intelligent baselines, SLA monitoring, and alerts
                                                                                  • 5. DataWorks Data Quality monitoring
                                                                                    • 6. Table-level and field-level data lineage
                                                                                      • 7. Strong and weak data quality rules
                                                                                        - Data Security and Compliance
                                                                                        • 1. Principle of least privilege
                                                                                          • 2. DataWorks Security Center
                                                                                            • 3. Cloud shared responsibility model
                                                                                              • 4. Encryption in transit using TLS and encryption at rest using KMS
                                                                                                • 5. Dynamic data masking
                                                                                                  • 6. ActionTrail audit logs and abnormal behavior alerts
                                                                                                    • 7. Data classification and sensitivity levels
                                                                                                      • 8. Personal Information Protection Law and Data Security Law of China
                                                                                                        • 9. Resource Access Management users, roles, policies, and MFA
                                                                                                          • 10. Key Management Service default keys and Bring Your Own Key
                                                                                                            • 11. Identity authentication, access control, data protection, and auditing
                                                                                                              • 12. Data Lake Formation unified permissions and column-level access control
                                                                                                                Big Data Fundamentals and Cloud Data Platforms15%- Understand Cloud Big Data Architectures and Product Portfolio
                                                                                                                • 1. Storage-compute separation architecture
                                                                                                                  • 2. MaxCompute, Hologres, EMR, DMS, AnalyticDB, and DTS
                                                                                                                    • 3. Data Lake Formation unified metadata management
                                                                                                                      • 4. Cloud big data architecture advantages and serverless computing
                                                                                                                        • 5. OpenLake and ApsaraDB architectures and use cases
                                                                                                                          • 6. Cloud-native and open-source-compatible computing engines
                                                                                                                            - Understand Core Big Data Concepts
                                                                                                                            • 1. MapReduce and the Hadoop ecosystem
                                                                                                                              • 2. Apache Flink stream processing and unified stream and batch processing
                                                                                                                                • 3. OLTP and OLAP concepts and differences
                                                                                                                                  • 4. Apache Spark in-memory computing
                                                                                                                                    • 5. Traditional data processing bottlenecks and distributed computing
                                                                                                                                      • 6. Data warehouse, data lake, and lakehouse architectures
                                                                                                                                        Data Modeling, Development, and Applications30%- Big Data and AI Integration
                                                                                                                                        • 1. MaxCompute public models, token billing, and computing-unit billing
                                                                                                                                          • 2. Milvus, Hologres vector search, and OpenSearch
                                                                                                                                            • 3. Retrieval-augmented generation workflow
                                                                                                                                              • 4. Large language model hallucinations and RAG mitigation
                                                                                                                                                • 5. Embeddings and vector search
                                                                                                                                                  • 6. MaxCompute AI Function and SQL- or Python-based AI tasks
                                                                                                                                                    • 7. Platform for AI, model training, PAI-EAS deployment, and remote models
                                                                                                                                                      • 8. Combining full-text search and vector search
                                                                                                                                                        • 9. Generative AI, traditional AI, LLMs, and multimodal LLMs
                                                                                                                                                          • 10. AI_GENERATE and ML_PREDICT functions
                                                                                                                                                            • 11. Hologres scalar and vector search and AI functions
                                                                                                                                                              • 12. MaxFrame distributed Python engine
                                                                                                                                                                - Data Modeling and Development
                                                                                                                                                                • 1. Directed acyclic graph scheduling and task orchestration
                                                                                                                                                                  • 2. DataWorks Data Agent and AI-assisted development
                                                                                                                                                                    • 3. Dimensional modeling, fact tables, and dimension tables
                                                                                                                                                                      • 4. Dependency management, automatic retries, data backfill, and idempotency
                                                                                                                                                                        • 5. DataWorks data development and scheduling
                                                                                                                                                                          • 6. Consistent metric definitions
                                                                                                                                                                            • 7. Star schemas and snowflake schemas
                                                                                                                                                                              • 8. Layered data warehouse architecture: ODS, DWD, DIM, DWS, and ADS
                                                                                                                                                                                - Data Applications and Visualization
                                                                                                                                                                                • 1. Data consumption requirements for operations teams, management, and developers
                                                                                                                                                                                  • 2. Data push notifications through DingTalk, Lark, and email
                                                                                                                                                                                    • 3. DataV real-time visualization dashboards
                                                                                                                                                                                      • 4. Dashboard dimensions, measures, charts, and Smart Q
                                                                                                                                                                                        • 5. Quick BI self-service business intelligence
                                                                                                                                                                                          • 6. DataWorks DataService Studio and RESTful APIs
                                                                                                                                                                                            • 7. Analytical reports and large-screen dashboards
                                                                                                                                                                                              • 8. Data as a Service

                                                                                                                                                                                                Alibaba Data-ACA Exam: Your Questions, Answered

                                                                                                                                                                                                The Data-ACA exam is how Alibaba decides who earns the Alibaba Certification certification, positioned at the Associate level. It checks whether you can apply the Alibaba Cloud Certified Data Engineer - Associate Certification objectives to realistic problems — the skill employers are actually hiring for. It also sits within a broader certification ecosystem covering Alibaba Cloud Certified Data Engineer (Associate), so the effort compounds across your career. In a crowded global market, that badge is a competitive edge you can point to.

                                                                                                                                                                                                The Alibaba Cloud Certified Data Engineer - Associate Certification blueprint spans 4 domains, led by Data Integration, Storage, and Processing (30%), Big Data Fundamentals and Cloud Data Platforms (15%), and Data Governance and Security (25%). Use the weightings as a budget: heavier domains earn heavier slices of your week. The full topic breakdown is in the exam topics section above — plan against it, not against hunches.

                                                                                                                                                                                                The Alibaba Cloud Certified Data Engineer - Associate Certification exam fits 50 questions into 60 minutes. Do the arithmetic before test day: minutes divided by questions is your per-item budget, and anything eating double its budget gets flagged for the end-of-exam sweep. Rehearse the pacing against a live timer — every PracticeMaterial engine session enforces one — until finishing with spare review time is routine.

                                                                                                                                                                                                Passing Alibaba Cloud Certified Data Engineer - Associate Certification takes 80/100, and each attempt costs USD 200 — retakes included, at full price. The rational strategy is arriving over-prepared: drill with PracticeMaterial practice questions until your timed scores clear the mark several sessions running, then register. You're not being timid; you're refusing to buy the same exam twice.

                                                                                                                                                                                                Alibaba lists the Alibaba Cloud Certified Data Engineer - Associate Certification question formats as: Single-choice, Multiple-choice. Format shapes tactics — find the real question sentence inside long scenario stems before reading the details, and re-verify every selection on multi-answer items. PracticeMaterial's 0 practice questions exercise these formats until they feel like old acquaintances.

                                                                                                                                                                                                The Data-ACA exam is available in English. Choose whichever language keeps your reading fastest under the clock — in a timed exam, slow comprehension taxes every single question. Testing in English? Daily work with PracticeMaterial's English Data-ACA practice questions doubles as terminology training.

                                                                                                                                                                                                The certification earned via the Alibaba Cloud Certified Data Engineer - Associate Certification exam remains valid for 2 years from the date the certificate is claimed. Mark the expiry date the day you pass and research the recertification path well before it approaches — a planned renewal is an errand; an expired credential is a project. Alibaba owns these rules, so confirm the current ones on the official certification page when your window nears.

                                                                                                                                                                                                All three carry the same 0 expert-written questions — you're choosing how you want to live with the material:

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                                                                                                                                                                                                • Online Test Engine — study from any browser on Windows, Mac, Android, or iOS; test history and performance review included, and once you've studied online you can keep going even without a connection.

                                                                                                                                                                                                Many candidates mix them — PDF for notes, an engine for timed rehearsal.

                                                                                                                                                                                                Yes. PracticeMaterial's free Alibaba Cloud Certified Data Engineer - Associate Certification PDF demo contains genuine sample questions with verified answers, so you can judge quality firsthand. Every purchase includes 365 days of free updates, and renewing after expiry costs 50% of the regular price from your member zone. Look before you buy — material this confident has nothing to hide.

                                                                                                                                                                                                Continuously. As Alibaba adjusts the Alibaba Cloud Certified Data Engineer - Associate Certification exam, our experts revise the bank to match, with customer feedback feeding the same loop. Updates are free for 365 days through your member zone; follow the New Releases section or the PracticeMaterial newsletter, and re-verify your version 3-4 days before your exam. Expired products repurchase at 50% off to restart the service.

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