Alibaba Data-ACA exam - in .pdf

Data-ACA pdf
  • Exam Code: Data-ACA
  • Exam Name: Alibaba Cloud Certified Data Engineer - Associate Certification Exam
  • Updated: Oct 27, 2026
  • Q & A: 0 Questions and Answers
  • PDF Price: $888.00
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  • Exam Code: Data-ACA
  • Exam Name: Alibaba Cloud Certified Data Engineer - Associate Certification Exam
  • Updated: Oct 27, 2026
  • Q & A: 0 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
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Alibaba Data-ACA exam - Testing Engine

Data-ACA Testing Engine
  • Exam Code: Data-ACA
  • Exam Name: Alibaba Cloud Certified Data Engineer - Associate Certification Exam
  • Updated: Oct 27, 2026
  • Q & A: 0 Questions and Answers
  • Software Price: $888.00
  • Testing Engine

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Alibaba Data-ACA Exam Syllabus Topics:

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

                                                                                                                                                                                                Your Alibaba Cloud Certified Data Engineer - Associate Certification Questions Answered in Full

                                                                                                                                                                                                At present, the Data-ACA exam's passing score is 80/100, and registration costs USD 200. Since failing means registering again at full price, thorough preparation is the economical choice — and Alibaba can revise both figures, so confirm them officially before booking.

                                                                                                                                                                                                The Alibaba Cloud Certified Data Engineer - Associate Certification blueprint is built around these main domains:

                                                                                                                                                                                                • Data Governance and Security (25%)
                                                                                                                                                                                                • Data Modeling, Development, and Applications (30%)
                                                                                                                                                                                                • Data Integration, Storage, and Processing (30%)

                                                                                                                                                                                                Additional domains appear in the full official outline — our bank covers them all.

                                                                                                                                                                                                Honored in writing. If you fail the corresponding exam within 60 days of purchase, send us a scanned copy of your enrollment slip and your official Score Report PDF within two days of the exam date; verified claims are refunded in full within seven days. Exclusions: exams taken within three days of purchase, candidate names that differ from the payer, and free or expired products. You may also exchange your product for two others of equal value at no charge.

                                                                                                                                                                                                By a professional group with dedicated contribution — experienced engineers and educators in this industry who compile every Data-ACA question and verify every answer across the Alibaba Cloud Certified Data Engineer - Associate Certification objectives. Maintenance is continuous: as new technology standards and knowledge emerge, revisions follow, and each updated version is sent to your mailbox immediately, free for 365 days, with a 50% renewal discount for further partnership. Privacy is protected by principle — your information is classified and never sold or shared, so no one will call you to sell something after our cooperation. And preferential terms — bundle discounts on the three versions, irregular coupons, little gifts — thank you for your trust in return.

                                                                                                                                                                                                Alibaba publishes these prerequisites for the Alibaba Cloud Certified Data Engineer - Associate Certification: 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..

                                                                                                                                                                                                Verify the current requirements on the official certification page.

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                                                                                                                                                                                                Per the latest exam information, the Data-ACA exam contains 50 questions with 60 minutes minutes to complete them. The PC Test Engine lets you simulate a full test event under these conditions to check your progress.

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