Huawei H13-723-ENU Q&A - in .pdf

  • Exam Code: H13-723-ENU
  • Exam Name: HCIP-Big Data Developer
  • Updated: Sep 17, 2026
  • Q & A: 155 Questions and Answers
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  • Exam Code: H13-723-ENU
  • Exam Name: HCIP-Big Data Developer
  • Updated: Sep 17, 2026
  • Q & A: 155 Questions and Answers
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Huawei H13-723-ENU (HCIP-Big Data Developer) Exam is one of the most sought-after certifications in the field of big data development. H13-723-ENU exam is designed for professionals who want to advance their career in big data development and analytics. The HCIP-Big Data Developer certification is a testament to the candidate's skills and knowledge in developing, designing, and maintaining big data applications using Huawei’s FusionInsight HD and Hadoop ecosystems.

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HCIP-Big Data Developer V1.0 Exam is a comprehensive certification program that covers several topics, including the analysis and design of big data applications, as well as the management of big data solutions. Candidates who pass this certification exam will demonstrate advanced skills in Big Data development and be able to analyze and interpret complex data sets to provide solutions to their organization. The H13-723 certification demonstrates a candidate's ability to work independently or in a team environment, design, build, and maintain big data processing systems, and implement various algorithms and data structures for Big Data solutions.

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Huawei H13-723 (HCIP-Big Data Developer V1.0) Certification Exam is designed to test the skills and knowledge of individuals who want to become certified big data developers. H13-723-ENU exam is a globally recognized certification that validates professionals’ expertise in big data development using the Huawei FusionInsight HD big data platform. H13-723-ENU exam tests the candidate's ability to design and develop big data solutions, perform data analysis, and manage and maintain big data systems.

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Huawei H13-723-ENU Exam Syllabus Topics:

SectionWeightObjectives
Big Data Real-time Retrieval Scenario-based Solution30%- Real-time retrieval optimization
- Elasticsearch and real-time search
- HBase architecture and development
- GaussDB(DWS) and distributed query
Big Data Real-time Stream Computing Scenario-based Solution30%- Flink stream processing framework
- Flume and Kafka data ingestion
- Stream solution deployment and tuning
- Spark Streaming and Structured Streaming
Big Data Offline Batch Processing Scenario-based Solution25%- Data ingestion tools: Loader, Sqoop, Kettle
- Spark SQL and batch processing
- HDFS and Hive principles and usage
- Offline solution design and optimization
Big Data Application Development Overall Guide15%- Application development fundamentals
- Big data concepts and architecture
- Scenario-based big data solutions overview
- Mainstream big data technologies and ecosystems

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