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The ACA-BigData1 certification exam is targeted towards professionals who work with big data technology, such as data analysts, data scientists, developers, and architects. ACA Big Data Certification Exam certification is ideal for individuals who are looking to enhance their skills and knowledge in big data technology and its related fields. ACA Big Data Certification Exam certification exam consists of multiple-choice questions and has a duration of 90 minutes. ACA-BigData1 exam is conducted online, and candidates can take it from anywhere in the world. With the ACA-BigData1 certification, professionals can demonstrate their expertise and knowledge in big data technology, which can help them advance in their careers.

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Alibaba Cloud ACA-BigData1 certification exam is designed to test an individual's proficiency in big data analysis and processing. It is a widely recognized certification that validates an individual's skills and knowledge in handling big data through the Alibaba Cloud platform. ACA-BigData1 exam covers a range of topics, including big data concepts, data modeling, data processing, and data analysis.

Reference: https://edu.alibabacloud.com/certification/aca_bigdata?spm=a3c0i.11597324.1621765730.10.e69e4755kTNSGC

Alibaba Cloud ACA-BigData1 Exam Syllabus Topics:

SectionWeightObjectives
MaxCompute≈41%- Core concepts
  • 1. Projects, tables, partitions, resources, tasks
    - Data processing and usage
    • 1. SQL operations and query optimization
      • 2. Data upload and download (Tunnel, SDKs)
        • 3. UDF, UDAF, UDTF development
          - Security and management
          • 1. Project isolation and security levels
            • 2. Users, roles, ACL and policy authorization
              Distributed Systems Fundamentals- Distributed computing concepts
              • 1. Distributed file systems (HDFS concepts)
                • 2. Coordination services (ZooKeeper)
                  • 3. MapReduce fundamentals
                    • 4. Cluster resource management (YARN)
                      E-MapReduce (EMR)- Operations
                      • 1. Instance types and pricing models
                        • 2. Common big data application scenarios
                          - Cluster and ecosystem components
                          • 1. Cluster deployment and scaling
                            • 2. Spark, Hadoop, Kafka, ZooKeeper basics
                              DataWorks- Data development and orchestration
                              • 1. Data Studio usage
                                • 2. Data integration workflows
                                  • 3. Scheduling and O&M monitoring

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