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AWS Certified Data Analytics Study Guide: Specialty (DAS-C01)

(DAS-C01.AE1) / ISBN : 978-1-64459-269-4
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About This Course

Gain hands-on experience to pass the AWS DAS-C01 exam with the AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) course and lab. Interactive chapters comprehensively cover DAS-C01 exam objectives and impart skills required to design, build, secure, and maintain analytics solutions on AWS that are efficient, cost-effective, and secure. The AWS Data Analytics course has the best study resources to help you understand the collection system that addresses the key properties of data, such as order, format, and compression.

Skills You’ll Get

The AWS Certified Data Analytics - Specialty certification is for individuals performing data analytics-focused role. The AWS Data Analytics certification exam validates a candidate's ability to define AWS data analytics services, explain how AWS data analytics services fit in the data life cycle of collection, storage, processing, and visualization. The DAS-C01 exam focuses on the topics such as collection, storage and data management, processing, security, analysis and visualization.
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1

Introduction

  • What Does This Course Cover?
  • Preparing for the Exam
  • Registering for the Exam
  • Studying for the Exam
  • Exam Objectives
2

History of Analytics and Big Data

  • Evolution of Analytics Architecture Over the Years
  • The New World Order
  • Analytics Pipeline
  • The Big Data Reference Architecture
  • Data Lakes and their Relevance in Analytics
  • Building a Data Lake on AWS
  • Using Lake Formation to build a Data Lake on AWS
  • Exam Objectives
  • References
3

Data Collection

  • AWS IoT
  • Amazon Kinesis
  • AWS Glue
  • Amazon SQS
  • Amazon Data Migration Service
  • AWS Data Pipeline
  • Large-Scale Data Transfer Solutions
  • Summary
  • References
  • Exercises & Workshops
4

Data Storage

  • Introduction
  • Amazon S3
  • Amazon S3 Glacier
  • Amazon DynamoDB
  • Amazon DocumentDB
  • Graph Databases and Amazon Neptune
  • Storage Gateway
  • Amazon EFS
  • Amazon FSx for Lustre
  • AWS Transfer for SFTP
  • Summary
  • Exercises
  • Further Reading
  • References
5

Data Processing and Analysis

  • Introduction
  • Types of Analytical Workloads
  • Amazon Athena
  • Amazon EMR
  • Amazon Elasticsearch Service
  • Amazon Redshift
  • Kinesis Data Analytics
  • Comparing Batch Processing Services
  • Comparing Orchestration Options on AWS
  • Summary
  • Exam Essentials
  • Exercises
  • References
6

Data Visualization

  • Introduction
  • Data Consumers
  • Data Visualization Options
  • Amazon QuickSight
  • Other Visualization Options
  • Predictive Analytics
  • Summary
  • Exam Essentials
  • Exercises
  • References
  • Additional Material
7

Data Security

  • Introduction
  • Shared Responsibility Model
  • Security Services on AWS
  • AWS IAM Overview
  • Amazon EMR Security
  • Amazon S3 Security
  • Amazon Athena Security
  • Amazon Redshift Security
  • Amazon Elasticsearch Security
  • Amazon Kinesis Security
  • Amazon QuickSight Security
  • Amazon DynamoDB Security
  • Summary
  • Exam Essentials
  • Exercises/Workshops
  • References and Further Reading

1

Data Collection

  • Creating a Kinesis SQL Application
  • Creating a Kinesis Data Stream
  • Creating a Kinesis Firehose Delivery Stream
  • Using AWS Glue
  • Creating an SQS Queue
2

Data Storage

  • Enabling Access Logging for an Amazon S3 Bucket
  • Creating an S3 Bucket and Enabling Versioning on it
  • Creating an Amazon S3 Glacier Vault
  • Creating a DAX Cluster
  • Enabling DynamoDB Streams
  • Creating a DynamoDB Table and Writing Data to it
  • Creating an Amazon EFS
3

Data Processing and Analysis

  • Using Amazon Athena
  • Creating a VPC Endpoint in Amazon OpenSearch Service
  • Creating an Amazon Redshift Cluster
4

Data Security

  • Creating an IAM Role
  • Creating an IAM Group
  • Creating an IAM User
  • Specifying Server-Side Encryption in S3 with AWS KMS (SSE-KMS)
  • Configuring Block Public Access Settings for your S3 Account
  • Creating an Encrypted Table in DynamoDB

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  • A minimum of 5 years of experience with common data analytics technologies
  • At least 2 years of hands-on experience working on AWS
  • Experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions

USD 300

The exam contains 65 questions.

180 minutes

750

(on a scale of 100-1000)

In the event that you do not pass to pass an AWS Certification exam, you may retake the exam subject to the following conditions:

  1. You must wait 14 days from the day you fail to take the exam again.
  2. Candidates must pay the exam price each time they attempt the exam.
  3. AWS beta examinations may only be taken one (1) time by each candidate.
  4. If a candidate has passed an exam, he/she cannot take it again unless their current certification has expired.
  5. A test result found to be in violation of the retake policy will be marked invalid, which will result in no credit awarded for the test taken. Repeat violators will be banned from participation in the AWS Certification Program.

Three years.

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