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Last Updated: Sep 12, 2026
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Huawei H13-723_V2.0 (HCIP-Big Data Developer V2.0) Certification Exam is an advanced-level certification exam that assesses a candidate's knowledge and skills in big data development. H13-723_V2.0 exam is designed for professionals who are looking to build a career in big data development or have experience in the field and want to validate their skills. The Huawei H13-723_V2.0 exam is a highly sought-after certification that demonstrates a candidate's proficiency in big data development.
Huawei H13-723_V2.0 Exam covers a wide range of topics related to big data development, such as big data architecture design, distributed computing, data analysis, and data security. H13-723_V2.0 exam is designed to test the candidate's ability to solve real-world problems using big data technologies and tools, including Hadoop, Spark, and Hive.
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The HCIP-Big Data Developer V2.0 exam is a comprehensive certification exam that tests the candidate's ability to design, develop, deploy, and maintain big data applications. HCIP-Big Data Developer V2.0 certification is recognized globally and is highly valued by employers. H13-723_V2.0 exam is designed for professionals who have experience in big data development and want to enhance their skills and knowledge in this field. Passing the exam validates the candidate's proficiency in big data development and opens up new career opportunities.
The HCIP-Big Data Developer V2.0 certification exam is a highly sought-after certification for IT professionals who are looking to establish themselves as experts in the field of big data. HCIP-Big Data Developer V2.0 certification exam is offered by Huawei, a leading provider of networking and telecommunications equipment and services.
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| Section | Weight | Objectives |
|---|---|---|
| Big Data Application Development Overall Guide | 15% | - Application development process and specifications - Mainstream big data technologies and ecosystem - Scenario-based solution design overview - FusionInsight HD architecture and components |
| Big Data Offline Batch Processing Scenario-based Solution | 25% | - Spark Core, Spark SQL and Catalyst optimization - HDFS and YARN principles and configuration - Hive development, optimization and ACID transactions - Data ingestion tools: Loader, Sqoop, Flume |
| Big Data Real-time Stream Computing Scenario-based Solution | 30% | - Kafka architecture, transactions and configuration - Apache Flink: event time, watermark, windowing and state management - Flink SQL and complex event processing - Spark Structured Streaming fundamentals |
| Big Data Real-time Retrieval Scenario-based Solution | 30% | - Elasticsearch indexing, query and cluster management - Apache Phoenix and secondary indexes - CarbonData and GaussDB(DWS) basics - HBase architecture, row-key design and optimization |
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