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The HCIP-Big Data Developer V2.0 certification exam consists of theoretical knowledge and practical skills. Candidates are required to pass a written exam and a practical exam. The written exam tests the candidate's theoretical knowledge, while the practical exam tests the candidate's ability to apply the knowledge to real-world scenarios.

Huawei H13-723_V2.0 (HCIP-Big Data Developer V2.0) Certification Exam is an advanced-level certification that enables candidates to validate their skills and knowledge in big data development. HCIP-Big Data Developer V2.0 certification is designed for professionals who want to enhance their expertise in big data technology and develop solutions based on big data platforms. H13-723_V2.0 exam is intended to test candidates' ability to design, develop, and maintain big data solutions using a variety of tools and technologies.

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The Huawei H13-723_V2.0 exam is aimed at professionals who work with big data and want to enhance their skills and knowledge in this field. It is also suitable for individuals who want to demonstrate their expertise in big data development and enhance their career prospects. The HCIP-Big Data Developer V2.0 certification is recognized globally and is highly valued by employers in the IT industry.

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Huawei H13-723_V2.0 (HCIP-Big Data Developer V2.0) exam is an excellent opportunity for individuals who want to develop their skills and knowledge in the field of big data. With no pre-requisites, this certification is available to anyone who is passionate about big data, and is interested in pursuing a career in this exciting and growing field.

Huawei H13-723_V2.0 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Big Data Real-time Retrieval Scenario-based Solution30%- HBase architecture, row-key design and optimization
- CarbonData and GaussDB(DWS) basics
- Apache Phoenix and secondary indexes
- Elasticsearch indexing, query and cluster management
Topic 2: Big Data Real-time Stream Computing Scenario-based Solution30%- Flink SQL and complex event processing
- Kafka architecture, transactions and configuration
- Spark Structured Streaming fundamentals
- Apache Flink: event time, watermark, windowing and state management
Topic 3: Big Data Application Development Overall Guide15%- FusionInsight HD architecture and components
- Application development process and specifications
- Scenario-based solution design overview
- Mainstream big data technologies and ecosystem
Topic 4: Big Data Offline Batch Processing Scenario-based Solution25%- Data ingestion tools: Loader, Sqoop, Flume
- HDFS and YARN principles and configuration
- Hive development, optimization and ACID transactions
- Spark Core, Spark SQL and Catalyst optimization

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