AWS DAS-C01 (Data Analytics Specialty) Certification Exam Syllabus

DAS-C01 Dumps Questions, DAS-C01 PDF, Data Analytics Specialty Exam Questions PDF, AWS DAS-C01 Dumps Free, Data Analytics Specialty Official Cert Guide PDFThe AWS DAS-C01 exam preparation guide is designed to provide candidates with necessary information about the Data Analytics Specialty exam. It includes exam summary, sample questions, practice test, objectives and ways to interpret the exam objectives to enable candidates to assess the types of questions-answers that may be asked during the AWS Certified Data Analytics - Specialty exam.

It is recommended for all the candidates to refer the DAS-C01 objectives and sample questions provided in this preparation guide. The AWS Data Analytics Specialty certification is mainly targeted to the candidates who want to build their career in Specialty domain and demonstrate their expertise. We suggest you to use practice exam listed in this cert guide to get used to with exam environment and identify the knowledge areas where you need more work prior to taking the actual AWS Certified Data Analytics - Specialty exam.

AWS DAS-C01 Exam Summary:

Exam Name
AWS Certified Data Analytics - Specialty (Data Analytics Specialty)
Exam Code DAS-C01
Exam Price $300 USD
Duration 180 minutes
Number of Questions 65
Passing Score 750 / 1000
Recommended Training / Books Data Analytics Fundamentals
Big Data on AWS
Schedule Exam PEARSON VUE
Sample Questions AWS DAS-C01 Sample Questions
Recommended Practice AWS Certified Data Analytics - Specialty Practice Test

AWS Data Analytics Specialty Syllabus:

Section Objectives Weight
Collection - Determine the operational characteristics of the collection system
- Select a collection system that handles the frequency, volume, and source of data
- Select a collection system that addresses the key properties of data, such as order, format, and compression
18%
Storage and Data Management - Determine the operational characteristics of a storage solution for analytics
- Determine data access and retrieval patterns
- Select an appropriate data layout, schema, structure, and format
- Define a data lifecycle based on usage patterns and business requirements
- Determine an appropriate system for cataloging data and managing metadata
22%
Processing - Determine appropriate data processing solution requirements
- Design a solution for transforming and preparing data for analysis
- Automate and operationalize a data processing solution
24%
Analysis and Visualization - Determine the operational characteristics of an analysis and visualization solution
- Select the appropriate data analysis solution for a given scenario
- Select the appropriate data visualization solution for a given scenario
18%
 Security - Select appropriate authentication and authorization mechanisms
- Apply data protection and encryption techniques
- Apply data governance and compliance controls
18%
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