Cover image for AWS Certified Data Analytics Study Guide

AWS Certified Data Analytics Study Guide

Release Date: 2020/12/01
ISBN: 9781119649472
Topic:
0%
19
Chapters
0-1
Hours read
0k
Total Words
    Start Reading Now    
       Add to Wishlist       
View table of contents

Move your career forward with AWS certification! Prepare for the AWS Certified Data Analytics Specialty Exam with this thorough study guide

This comprehensive study guide will help assess your technical skills and prepare for the updated AWS Certified Data Analytics exam. Earning this AWS certification will confirm your expertise in designing and implementing AWS services to derive value from data. The AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam is designed for business analysts and IT professionals who perform complex Big Data analyses.

This AWS Specialty Exam guide gets you ready for certification testing with expert content, real-world knowledge, key exam concepts, and topic reviews. Gain confidence by studying the subject areas and working through the practice questions. Big data concepts covered in the guide include:

  • Collection
  • Storage
  • Processing
  • Analysis
  • Visualization
  • Data security

AWS certifications allow professionals to demonstrate skills related to leading Amazon Web Services technology. The AWS Certified Data Analytics Specialty (DAS-C01) Exam specifically evaluates your ability to design and maintain Big Data, leverage tools to automate data analysis, and implement AWS Big Data services according to architectural best practices. An exam study guide can help you feel more prepared about taking an AWS certification test and advancing your professional career. In addition to the guide’s content, you’ll have access to an online learning environment and test bank that offers practice exams, a glossary, and electronic flashcards.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. Acknowledgments
  6. About the Author
  7. About the Technical Editor
  8. Introduction
    1. What Does This Book Cover?
    2. Preparing for the Exam
    3. Registering for the Exam
    4. Studying for the Exam
    5. The Night before the Exam
    6. During the Exam
    7. Interactive Online Learning Environment and Test Bank
    8. Exam Objectives
    9. Assessment Test
    10. Answers to the Assessment Test
  9. Chapter 1: History of Analytics and Big Data
    1. Evolution of Analytics Architecture Over the Years
    2. The New World Order
    3. Analytics Pipeline
    4. The Big Data Reference Architecture
    5. Data Lakes and Their Relevance in Analytics
    6. Building a Data Lake on AWS
    7. Using Lake Formation to Build a Data Lake on AWS
    8. Exam Objectives
    9. Assessment Test
    10. References
  10. Chapter 2: Data Collection
    1. Exam Objectives
    2. AWS IoT
    3. Amazon Kinesis
    4. AWS Glue
    5. Amazon SQS
    6. Amazon Data Migration Service
    7. AWS Data Pipeline
    8. Large-Scale Data Transfer Solutions
    9. Summary
    10. Review Questions
    11. References
    12. Exercises & Workshops
  11. Chapter 3: Data Storage
    1. Introduction
    2. Amazon S3
    3. Amazon S3 Glacier
    4. Amazon DynamoDB
    5. Amazon DocumentDB
    6. Graph Databases and Amazon Neptune
    7. Storage Gateway
    8. Amazon EFS
    9. Amazon FSx for Lustre
    10. AWS Transfer for SFTP
    11. Summary
    12. Exercises
    13. Review Questions
    14. Further Reading
    15. References
  12. Chapter 4: Data Processing and Analysis
    1. Introduction
    2. Types of Analytical Workloads
    3. Amazon Athena
    4. Amazon EMR
    5. Amazon Elasticsearch Service
    6. Amazon Redshift
    7. Kinesis Data Analytics
    8. Comparing Batch Processing Services
    9. Comparing Orchestration Options on AWS
    10. Summary
    11. Exam Essentials
    12. Exercises
    13. Review Questions
    14. References
  13. Chapter 5: Data Visualization
    1. Introduction
    2. Data Consumers
    3. Data Visualization Options
    4. Amazon QuickSight
    5. Other Visualization Options
    6. Predictive Analytics
    7. Summary
    8. Exam Essentials
    9. Exercises
    10. Review Questions
    11. References
    12. Additional Reading Material
  14. Chapter 6: Data Security
    1. Introduction
    2. Shared Responsibility Model
    3. Security Services on AWS
    4. AWS IAM Overview
    5. Amazon EMR Security
    6. Amazon S3 Security
    7. Amazon Athena Security
    8. Amazon Redshift Security
    9. Amazon Elasticsearch Security
    10. Amazon Kinesis Security
    11. Amazon QuickSight Security
    12. Amazon DynamoDB Security
    13. Summary
    14. Exam Essentials
    15. Exercises/Workshops
    16. Review Questions
    17. References and Further Reading
  15. Appendix: Answers to Review Questions
    1. Chapter 1: History of Analytics and Big Data
    2. Chapter 2: Data Collection
    3. Chapter 3: Data Storage
    4. Chapter 4: Data Processing and Analysis
    5. Chapter 5: Data Visualization
    6. Chapter 6: Data Security
  16. Index
  17. Online Test Bank
    1. Register and Access the Online Test Bank
  18. End User License Agreement
3.141.7.194