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The AWS Certified Big Data - Specialty certification exam is a rigorous and comprehensive assessment of an individual's skills and expertise in designing and implementing big data solutions within the AWS ecosystem. It is a valuable credential for professionals seeking to enhance their careers in the field of big data and cloud computing.
Reference: https://aws.amazon.com/certification/certified-big-data-specialty/
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Amazon AWS-Certified-Big-Data-Specialty (AWS Certified Big Data - Specialty) Exam is a certification exam offered by Amazon Web Services (AWS) for professionals who work with Big Data. AWS-Certified-Big-Data-Specialty-KR exam is designed to validate the skills and knowledge of candidates in the field of Big Data and its related technologies. AWS-Certified-Big-Data-Specialty-KR exam covers a wide range of topics, including data collection, storage, processing, analysis, and visualization, as well as data security, networking, and architecture.
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Amazon AWS-Certified-Big-Data-Specialty Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Processing | 17% | - Select suitable processing technologies for workloads - Optimize operational characteristics of processing systems - Design and architect scalable processing solutions |
| Data Security | 20% | - Determine encryption requirements and implementation - Ensure data integrity and compliance - Implement data governance and access controls - Apply security best practices across data lifecycle |
| Visualization | 12% | - Select appropriate output and visualization techniques - Design and build visualization platforms - Optimize operational characteristics of visualization systems |
| Storage | 17% | - Analyze data access and retrieval patterns - Choose appropriate data structures and storage formats - Evaluate cataloging and metadata management mechanisms - Determine and optimize storage operational characteristics |
| Analysis | 17% | - Optimize performance and cost of analysis workflows - Determine analysis tools and techniques - Design and implement analytical solutions |
| Collection | 17% | - Identify required properties: order, structure, metadata - Determine operational characteristics of collection systems - Select appropriate ingestion systems for data type and change frequency - Explain durability and availability of ingestion approaches |
