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Amazon AWS-Big-Data-Specialty日本語 Exam Overview:
| Certification Vendor: | Amazon Web Services (AWS) |
| Exam Name: | AWS Certified Data Analytics - Specialty (formerly AWS Certified Big Data - Specialty) |
| Exam Number: | BDS-C00 (legacy) / DAS-C01 (current equivalent) |
| Exam Format: | Multiple Choice, Multiple Response |
| Passing Score: | 750 (scaled score out of 1000) |
| Real Exam Qty: | 65 (multiple choice and multiple response) |
| Exam Price: | $300 USD |
| Available Languages: | English, Japanese, Korean, Simplified Chinese |
| Certificate Validity Period: | 3 years |
| Related Certifications: | AWS Certified Solutions Architect - Associate AWS Certified Data Engineer - Associate AWS Certified Machine Learning - Specialty |
| Exam Duration: | 180 minutes |
| Recommended Training: | AWS Skill Builder Exam Prep: AWS Certified Data Analytics - Specialty |
| Exam Registration: | AWS Certification Exam Page AWS Certification Official Registration |
| Sample Questions: | Amazon AWS-Big-Data-Specialty日本語 Sample Questions |
| Exam Way: | Online proctored exam or test center (onsite) |
| Pre Condition: | Recommended: 5+ years of data analytics experience and at least 2 years of hands-on experience using AWS services for big data or analytics workloads. |
| Official Syllabus URL: | https://aws.amazon.com/certification/certified-data-analytics-specialty/ |
AWS Big Data Specialty Exam Syllabus Topics:
| Section | Objectives | Weight |
|---|---|---|
| Processing | -Identify the appropriate data processing technology for a given scenario -Determine how to design and architect the data processing solution -Determine the operational characteristics of the solution implemented | 17% |
| Storage | -Determine and optimize the operational characteristics of the storage solution -Determine data access and retrieval patterns -Evaluate mechanisms for capture, update, and retrieval of catalog entries -Determine appropriate data structure and storage format | 17% |
| Visualization | -Determine the appropriate techniques for delivering the results/output -Determine how to design and create the Visualization platform -Determine and optimize the operational characteristics of the Visualization system | 12% |
| Collection | -Determine the operational characteristics of the collection system -Select a collection system that handles the frequency of data change and type of data being ingested -Identify the properties that need to be enforced by the collection system: order, data structure, metadata, etc. -Explain the durability and availability characteristics for the collection approach | 17% |
| Data Security | -Determine encryption requirements and/or implementation technologies -Choose the appropriate technology to enforce data governance -Identify how to ensure data integrity -Evaluate regulatory requirements | 20% |
| Analysis | -Determine the tools and techniques required for analysis -Determine how to design and architect the analytical solution -Determine and optimize the operational characteristics of the Analysis | 17% |
AWS Certified Big Data - Specialty Exam Overview
AWS Certified Big Data - Specialty Exam Overview:
- Passing Score: 75-80%
- Registration Fee: 300 USD
- Length of Examination: 170 minutes
- Format: Multiple choice, multiple answer
Benefits of having AWS Certified Big Data - Specialty Certifications
The brand new AWS Big Data - Specialty certification will not only help you learn some new skills, it can position you for a higher paying job or help you transform your current role into a Big Data and Analytics professional. Get prepared to take this exam and become one of the very first AWS Big Data Certified professionals in the world using our AWS Certified Big Data - Specialty Exam Dumps
Amazon AWS-Big-Data-Specialty日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Collection | 18% | - Data ingestion and collection mechanisms
|
| Storage and Data Management | 22% | - Data lake and storage design
|
| Security | 18% | - Data security and governance
|
| Analysis and Visualization | 18% | - Analytics and BI tools
|
| Processing | 24% | - Data processing frameworks
|
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