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

  • Exam Code: AWS-Big-Data-Specialty
  • Exam Name: AWS Certified Big Data - Specialty
  • Updated: Jul 21, 2026
  • Q&As: 262 Questions and Answers

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About Amazon AWS-Big-Data-Specialty Real Exam

The AWS Certified Big Data - Specialty certification exam covers a wide range of topics related to Big Data, including data analysis, processing, storage, and management. It also includes topics such as data security, compliance, and governance. AWS-Big-Data-Specialty exam is designed to test the candidate's ability to design, implement, and maintain Big Data solutions using AWS services.

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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The AWS Certified Big Data - Specialty certification exam is an excellent way for professionals to validate their skills in designing and implementing AWS big data solutions. Candidates who successfully pass AWS-Big-Data-Specialty exam will demonstrate their expertise in AWS big data services and will be recognized as AWS Certified Big Data - Specialty professionals.

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

SectionWeightObjectives
Storage and Data Management22%- Data storage solutions
  • 1. Amazon DynamoDB for NoSQL analytics
    • 2. Amazon Redshift data warehousing
      • 3. Amazon S3 data lakes
        - Data catalog and governance
        • 1. Data partitioning and lifecycle management
          • 2. AWS Glue Data Catalog
            Processing24%- Real-time processing
            • 1. Amazon Kinesis Data Analytics
              • 2. AWS Lambda for event-driven processing
                - Data processing frameworks
                • 1. AWS Glue ETL jobs
                  • 2. Amazon EMR (Spark, Hadoop)
                    Security18%- Compliance and governance
                    • 1. AWS CloudTrail auditing
                      • 2. Data access control strategies
                        - Data protection
                        • 1. AWS IAM policies for analytics workloads
                          • 2. Encryption in transit and at rest (KMS)
                            Collection18%- Data collection patterns
                            • 1. Real-time data pipelines
                              • 2. Batch vs streaming ingestion
                                - Data ingestion services
                                • 1. AWS Glue streaming ingestion
                                  • 2. Amazon Kinesis Data Streams
                                    • 3. Amazon Kinesis Data Firehose
                                      Analysis and Visualization18%- Visualization
                                      • 1. Amazon QuickSight dashboards
                                        - Analytics tools
                                        • 1. Amazon Redshift Spectrum
                                          • 2. Amazon Athena

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