Amazon AWS-Big-Data-Specialty : AWS Certified Big Data - Specialty

  • Exam Code: AWS-Big-Data-Specialty
  • Exam Name: AWS Certified Big Data - Specialty
  • Updated: Jul 24, 2026
  • Q & A: 262 Questions and Answers

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The AWS Certified Big Data Specialty exam is one of the toughest exams and it requires you a lot of hands-on experience. It is advisable to have prior knowledge of Big Data technologies on AWS. The more experience you have, the more it is beneficial for you, Major challenging things which you can find in exam is about different scenario based questions, you must have strong understanding of Big Data.

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  • Search for AWS Certified Big Data - Specialty Certifications Exam
  • Select Date and Center of examination and confirm with payment value of 300$
  • Visit to website https://www.aws.training

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AWS Big Data Specialty Exam Syllabus Topics:

SectionObjectivesWeight
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%
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%
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%
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%
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%

Reference: https://d1.awsstatic.com/training-and-certification/docs-bigdata-spec/AWS%20Certified%20Big%20Data%20-%20Specialty_Exam%20Guide_v1.4_FINAL.pdf

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Amazon AWS-Big-Data-Specialty Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Domain 4: Data Analysis17%- Optimize query performance and analysis workflows
- Implement analytical operations and transformations
- Determine tools and techniques for analysis
- Design and architect analytical solutions
Topic 2: Domain 6: Data Security20%- Apply security best practices for big data workloads
- Determine encryption requirements and methods
- Implement data governance and access control
- Ensure data integrity and compliance
Topic 3: Domain 5: Data Visualization12%- Ensure accessibility and clarity of presented results
- Determine appropriate visualization techniques and tools
- Design and build visualization platforms and dashboards
- Optimize operational characteristics of visualization systems
Topic 4: Domain 3: Data Processing17%- Design and architect data processing solutions
- Determine operational characteristics of processing systems
- Select appropriate processing frameworks and services
- Optimize processing performance and cost efficiency
Topic 5: Domain 2: Data Storage17%- Identify data access and retrieval patterns
- Evaluate mechanisms for cataloging and metadata management
- Choose appropriate data structures and storage formats
- Determine and optimize operational characteristics of storage solutions
Topic 6: Domain 1: Data Collection17%- Identify properties including order, structure, and metadata
- Determine operational characteristics of collection systems
- Describe availability and durability of collection methods
- Select appropriate collection systems based on data type and frequency

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