To earn the AWS Certified Big Data - Specialty certification, candidates must pass the AWS-Big-Data-Specialty Exam. AWS Certified Big Data - Specialty certification is recognized by employers and industry experts as a validation of the candidate's skills and knowledge in big data analytics with AWS. It opens up new career opportunities and helps professionals stand out in a competitive job market. Overall, the AWS-Big-Data-Specialty Exam is a challenging but rewarding way for big data professionals to demonstrate their proficiency in AWS technologies and advance their careers.
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Amazon AWS-Big-Data-Specialty exam is designed for individuals who want to validate their knowledge and skills in working with big data solutions on the Amazon Web Services (AWS) platform. AWS Certified Big Data - Specialty certification is meant for professionals who are looking to enhance their career opportunities and demonstrate their expertise in big data technologies. The AWS Certified Big Data - Specialty exam is one of the most sought-after certifications in the IT industry.
Reference: https://aws.amazon.com/certification/certified-big-data-specialty/
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Amazon AWS-Certified-Big-Data-Specialty Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Security | 20% | - Select technologies for data governance and compliance - Evaluate regulatory and compliance requirements - Ensure data integrity and access control - Determine encryption requirements and implementation |
| Topic 2: Storage | 17% | - Select appropriate data structures and formats - Evaluate cataloging and metadata management mechanisms - Determine data access and retrieval patterns - Optimize operational characteristics of storage solutions |
| Topic 3: Processing | 17% | - Choose suitable processing technologies for given scenarios - Design and architect scalable data processing solutions - Assess operational characteristics of processing systems |
| Topic 4: Visualization | 12% | - Determine techniques for delivering analysis results - Optimize performance and usability of visualization systems - Design and build visualization platforms |
| Topic 5: Collection | 17% | - Determine operational characteristics of the collection system - Explain durability and availability of collection approaches - Identify properties to enforce: order, structure, metadata - Select appropriate collection system based on data type and frequency |
| Topic 6: Analysis | 17% | - Identify appropriate tools and techniques for analysis - Optimize operational characteristics of analysis workflows - Design and architect analytical solutions |
