AWS Certified Data Analytics Specialty Practice Exam - RETIRED

AWS Certified Data Analytics Specialty Practice Exam

The AWS Certified Data Analytics – Specialty exam was retired on April 8, 2024 - Learn more about AWS Certified Data Engineer - Associate (DEA-C01)

About AWS Certified Data Analytics Specialty Exam

The AWS Certified Data Analytics Specialty (DAS-C01) exam validates the candidate’s knowledge and understanding of using AWS services for planning, creating, securing, and maintaining analytics solutions that provide insight from data. However, this exam is also best for those in the data analytics-focused role.

Skills Acquired

The AWS Data Analytics Specialty Exam validates an examinee’s ability in -

• Defining AWS data analytics services and understanding how they combine with each other.
• Explaining the process of AWS data analytics services for fitting in the data lifecycle of collection, processing, storage, and visualization.

Recommended AWS Knowledge

• At least 5 years of experience with common data analytics technologies with minimum of 2 years of applied experience in operating AWS
• Experience and skills in working with AWS services for planning, creating, securing, and maintaining analytics solutions

Exam Details

• Exam Name: AWS Certified Data Analytics Specialty 
• Exam Code: DAS-C01
• Exam Format: Multiple Choice and Multiple responses, 
• Time Duration: 180 minutes
• Total Questions: 65 Questions
• Passing score: 750 (a score from 100-1000)
• Exam Fee: $300 USD
• Exam Language: English, Japanese, Korean, and Simplified Chinese

Course Outline

The AWS Data Analytics Specialty Exam covers the following topics - 

Module 1: Describe Collection (18%)

• Determining the operational characteristics of the collection system
• Selecting a collection system that handles the frequency, volume, and source of data
• Selecting a collection system that addresses the key properties of data, such as order, format, and compression

Module 2: Describe Storage and Data Management (22%)

• Determining the operational characteristics of a storage solution for analytics
• Determining data access and retrieval patterns
• Selecting suitable data layout, schema, structure, and format
• Defining a data lifecycle based on usage patterns and business requirements
• Determining a suitable system for cataloguing data and managing metadata

Module 3: Describe Processing (24%)

• Determining appropriate data processing solution requirements
• Designing a solution for transforming and preparing data for analysis
• Automating and operationalizing a data processing solution

Module 4: Analysis and Visualization (18%)

• Determining the operational characteristics of an analysis and visualization solution
• Selecting a suitable data analysis solution for a given scenario
• Selecting the appropriate data visualization solution for a given scenario

Module 5: Security (18%)

• 5.1 Selecting appropriate authentication and authorization mechanisms
• 5.2 Applying data protection and encryption methods
• 5.3 Applying data governance and compliance controls

What do we offer?

• Full-Length Mock Test with unique questions in each test set
• Practice objective questions with section-wise scores
• An in-depth and exhaustive explanation for every question
• Reliable exam reports evaluating strengths and weaknesses
• Latest Questions with an updated version
• Tips & Tricks to crack the test
• Unlimited access

What are our Practice Exams?

• Practice exams have been designed by professionals and domain experts that simulate real-time exam scenario.
• Practice exam questions have been created on the basis of content outlined in the official documentation.
• Each set in the practice exam contains unique questions built with the intent to provide real-time experience to the candidates as well as gain more confidence during exam preparation.
• Practice exams help to self-evaluate against the exam content and work towards building strength to clear the exam.
• You can also create your own practice exam based on your choice and preference 

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