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Updated: Jul 17, 2026
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The HCIA-Big Data certification is a professional certification targeted at candidates who have basic knowledge of the data center, as well as the basics of big data, data analysis, and data mining. HCIA-Big Data V3.0 certification is best suited for mid-level IT professionals who want to enhance their skills in the data science domain. H13-711_V3.0 exam tests candidates’ ability to design, deploy, maintain a big data platform, and manipulate big data analytically using Hadoop, Kafka, and Spark.
Huawei H13-711_V3.0-ENU (HCIA-Big Data V3.0) Certification Exam is a valuable certification for individuals who want to advance their careers in the field of big data. HCIA-Big Data V3.0 certification demonstrates that the candidate has the skills and knowledge needed to design and implement big data solutions. It also shows that the candidate is committed to staying up-to-date with the latest technologies and trends in the field of big data.
The H13-711_V3.0 (HCIA-Big Data V3.0) Certification Exam is an excellent opportunity for IT professionals to enhance their skills and knowledge in the field of big data. H13-711_V3.0 exam covers a range of topics, including big data concepts, architecture, processing, analysis, and application. By passing the exam, IT professionals can demonstrate their expertise in big data and enhance their career prospects.
Huawei H13-711_V3.0-ENU exam requires a thorough understanding of big data technologies, including Hadoop, Spark, Hive, HBase, and many others. H13-711_V3.0 exam covers the fundamentals of big data, including data modeling, data storage, data processing, analysis, and visualization. H13-711_V3.0 exam also includes questions on big data security, privacy, and compliance requirements. The HCIA-Big Data certification verifies that you have the skills and knowledge to design and implement big data solutions that are secure, efficient, and scalable.
| Certification Vendor: | Huawei |
| Exam Name: | Huawei Certified ICT Associate - Big Data V3.0 |
| Exam Number: | H13-711_V3.0-ENU |
| Exam Duration: | 90 minutes |
| Certificate Validity Period: | 3 years |
| Exam Format: | Single-choice, Multiple-choice, True/False, Fill-in-the-blank, Drag-and-drop |
| Real Exam Qty: | 60 |
| Exam Price: | USD 200 |
| Related Certifications: | HCIP-Big Data Developer HCIE-Big Data |
| Available Languages: | English, Chinese |
| Passing Score: | 600 / 1000 |
| Recommended Training: | Huawei FusionInsight MRS Documentation HCIA-Big Data V3.0 Official Training |
| Exam Registration: | Pearson VUE Registration Huawei Talent Official Portal |
| Sample Questions: | Huawei H13-711_V3.0 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE authorized test centers |
| Pre Condition: | No mandatory prerequisites; recommended basic Linux and Hadoop knowledge |
| Official Syllabus URL: | https://e.huawei.com/en/talent/cert/#/certDetail/H13-711_V3.0 |
| Section | Weight | Objectives |
|---|---|---|
| Security & Other Components | 8% | - Elasticsearch and Redis overview - LDAP and Kerberos authentication mechanism |
| Huawei Big Data Platform & Solutions | 7% | - FusionInsight/MRS architecture and components - Typical big data solutions and use cases |
| Data Warehouse & Query Engine | 18% | - Hive execution engines: MapReduce, Tez, Spark - File formats: ORC, Parquet, SequenceFile - Hive architecture, metastore, partitioning and bucketing |
| Data Integration & Streaming | 15% | - Flume log collection architecture and configuration - Loader data migration and synchronization - Kafka message queue principles and usage |
| Distributed Storage & Coordination | 20% | - ZooKeeper functions, architecture and application - HBase architecture, data model and row-key design - HDFS architecture, principles and operations |
| Big Data Industry Overview & Basic Concepts | 10% | - Development trends and characteristics of big data - Huawei Kunpeng big data ecosystem - Big data application scenarios and challenges |
| Distributed Computing Framework | 22% | - MapReduce programming model and workflow - Spark core concepts, RDD, DataFrame and Spark SQL - Flink stream processing fundamentals - YARN architecture, resource scheduling and management |
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