Exam Topics

As for Amazon DAS-C01, the vendor provides the learners with the guide that includes the detailed information about all its domains. All in all, the topics covered in the exam content are as follows:

• Storage and Data Management

  This domain evaluates the professionals’ skills in determining the operational characteristics of the given storage solution for analytics, defining a data lifecycle based on the business requirements & usage patterns, determining an appropriate system for managing Metadata and cataloging data, as well as selecting the appropriate data layout, format, structure & schema, and determining data access & retrieval patterns.

• Security

  The questions of the last objective are dedicated to validating the individuals’ understanding of selecting the appropriate authorization and authentication mechanisms, applying data compliance & governance controls, and applying data encryption & protection techniques.

• Analysis and Visualization

  This topic is all about the students’ ability to demonstrate a wide range of technical tasks related to visualization and analysis of data, including selecting the right data visualization & data analysis solutions for a specific scenario, as well as determining the operational features of visualization and analysis solution.

• Collection

  The first part requires that the candidates demonstrate their expertise in determining the operational characteristics of features of the collection system, selecting a collection system that addresses the main properties of data, such as compression, format, and order, as well as selecting a collection system, which handles the source, volume, and frequency of data.

• Processing

  In the framework of this subject area, the test takers have to perform their knowledge and skills in determining the proper data processing solution requirements, operationalizing & automating a data processing solution, designing a solution for preparing and transforming data for analysis, and more.

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AWS Data Analytics Specialty Training Courses

There are many courses available for candidates to prepare well for the certification exam. Two most popular options are as follows:

1. Big Data On AWS Training Course by AWS Training

This training presents test-takers with big data solutions such as Amazon Kinesis, Amazon Redshift, Amazon EMR, and others. One will learn more about how to use these tools effectively and process the required data using Hue and Hive. The applicants will also gain information about the following subjects, to name a few:

• Transferring, compressing, and ingesting data
• Selecting proper solutions for data storage
• Utilizing programming frameworks
• Visualization software

This 3-days course is available in different languages like English, French, German, Italian, Simplified Chinese, and many more. To help you grasp the topics better, it also involves practical labs.

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How to book the AWS Certified Data Analytics - Specialty (DAS-C01) Professional Exam

To apply for the AWS Certified Data Analytics - Specialty (DAS-C01) Professional Exam , You have to follow these steps:

• Step 1: Go to the AWS Certified Data Analytics - Specialty (DAS-C01) Professional Official Site
• Step 2: Read the instruction Carefully
• Step 3: Follow the given steps
• Step 4: Apply for the AWS-Certified Data Analytics - Specialty (DAS-C01)-Professional Exam

Reference: https://d1.awsstatic.com/training-and-certification/docs-data-analytics-specialty/AWS-Certified-Data-Analytics-Specialty-Exam-Guide_v1.0_08-23-2019_FINAL.pdf

Prerequisites

Amazon specifies the recommended knowledge and experience for taking the DAS-C01 exam. It is also required to have any associate-level certification or the AWS Certified Cloud Practitioner certificate. In terms of experience, the students for this test should have a minimum of five years of practical experience in working with analysis solutions on AWS and complex data analytics. The candidates need to possess the relevant expertise and familiarity with the AWS services for building, securing, designing, and maintaining analytics solutions.

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