AWS Certified Big Data - Specialty Certification

Video description

Expert tips, techniques, and best practices to pass the AWS Certified Big Data - Specialty exam

About This Video

  • Understand the importance of the AWS Certified Big Data - Specialty Certification exam for advancing in your career
  • Get to grips with the exam pattern and exam syllabus
  • Discover different types of cloud computing and their advantages

In Detail

This course covers all aspects of hosting big data on the Amazon Web Services (AWS) platform, and will prepare you to confidently perform distributed processing.

The course begins with an overview of exam details and the recommended AWS knowledge you need before starting the course. It then takes you through topics relating to big data on AWS such as cloud computing and deployment, databases and data warehousing in AWS, and AWS services for big data. Next, you’ll move on to learn about data collection within big data on AWS which will cover data producers and consumers, IoT and big data, and Kinesis Firehose. As you advance, you’ll get to grips with the storage and processing aspects of big data on AWS, covering DynamoDB, AWS aurora in big data, and Amazon EMR. Finally, you’ll delve into visualization and security, and create a project for analyzing large datasets.

By the end of this course, you will have learned about cloud-based big data solutions, and be able to use AWS Elastic MapReduce to process data and create big data environments.


This course is for anyone with the cloud practitioner or associate-level AWS certification and a minimum of 2 years’ experience in performing complex big data analysis, including solutions architects, SysOps administrators, data scientists, and data analysts. The course assumes an understanding of AWS security best practices and AWS service integration.

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Table of contents

  1. Chapter 1 : Exam Details
    1. Course Introduction
    2. Overview of Big Data on AWS Certification
    3. Objective of Big Data on AWS Certification Course
    4. Exam Pattern and Exam Syllabus
    5. Recommended AWS Knowledge
  2. Chapter 2 : Big Data on AWS Introduction
    1. Learning Objectives
    2. Cloud Computing Introduction, Advantages, and Types
    3. Cloud Deployment Models
    4. Cloud Service Categories
    5. AWS Cloud Platform
    6. AWS Cloud Architecture Design Principles - Part I
    7. AWS Cloud Architecture Design Principles - Part II
    8. Why AWS for Big Data - Reasons and Challenges
    9. Databases in AWS
    10. Data Warehousing in AWS
    11. Redshift, Kinesis, and EMR
    12. DynamoDB, Machine Learning, and Lambda
    13. Elastic Search Services and EC2
    14. Key Takeaways
  3. Chapter 3 : Big Data on AWS - Collection
    1. Learning Objective
    2. Amazon Kinesis and Kinesis Stream
    3. Kinesis Data Stream Architecture and Core Components
    4. Data Producer
    5. Data Consumer
    6. Kinesis Stream Emitting Data to AWS Services and Kinesis Connector Library
    7. Kinesis Firehose
    8. Demo - Put and Get Records from Kinesis Data Stream
    9. Transferring Data Using Lambda
    10. Amazon SQS Lifecycle and Architecture
    11. IoT and Big Data
    12. IoT Framework
    13. AWS Data Pipelines and Data Nodes
    14. Activity, Pre-Condition, and Schedule
    15. Demo - Importing Data from S3 into DynamoDB Using Data Pipeline
    16. Key Takeaways
  4. Chapter 4 : Big Data on AWS - Storage
    1. Learning Objective
    2. Amazon Glacier and Big Data
    3. DynamoDB Introduction
    4. DynamoDB and EMR
    5. DynamoDB Partitions and Distributions
    6. DynamoDB GSI LSI
    7. DynamoDB Stream and Cross-Region Replication
    8. DynamoDB Performance and Partition Key Selection
    9. Snowball and AWS Big Data
    10. AWS DMS
    11. AWS Aurora in Big Data
    12. Demo - Amazon Athena Interactive SQL Queries for Data in Amazon S3 Part I
    13. Demo - Amazon Athena Interactive SQL Queries for Data in Amazon S3 Part II
    14. Key Takeaways
  5. Chapter 5 : Big Data on AWS - Processing
    1. Learning Objective
    2. Amazon EMR
    3. Demo - Analysing Big Data with Amazon EMR
    4. Apache Hadoop
    5. EMR Architecture
    6. EMR Operations - Releases and Cluster
    7. EMR Operations - Choosing Instance and Monitoring
    8. Demo - Advanced EMR Setting Options
    9. Hive on EMR
    10. HBase with EMR
    11. Presto with EMR
    12. Spark with EMR
    13. EMR File Storage
    14. Demo - Analysing Large Datasets Using Hive and Spark
    15. AWS Lambda
    16. Key Takeaways
  6. Chapter 6 : Big Data on AWS - Analysis
    1. Learning Objective
    2. Redshift Intro and Use Cases
    3. Redshift Architecture
    4. MPP and Redshift in AWS Ecosystem
    5. Columnar Databases
    6. Redshift Table Design - Part I
    7. Redshift Table Design - Part II
    8. Demo - Generating Random Dataset in EC2 and Loading it in S3
    9. Demo - Redshift Maintenance and Operations
    10. Machine Learning Introduction
    11. Machine Learning Algorithm
    12. Amazon SageMaker
    13. Amazon Elasticsearch
    14. Amazon Elasticsearch Services
    15. Demo - Loading Datasets into Elasticsearch
    16. Logstash and RStudio
    17. Demo - Fetching the File and Analysing it using RStudio
    18. Athena
    19. Demo - Running Query on S3 using the Serverless Athena
    20. Demo - Creating a Redshift Cluster and Loading the Datasets into it from S3 - Part I
    21. Demo - Creating a Redshift Cluster and Loading the Datasets into it from S3 - Part II
    22. Key Takeaways
  7. Chapter 7 : Big Data on AWS - Visualization
    1. Learning Objective
    2. Amazon QuickSight
    3. Demo - Creating an Analysis with a Single Visual using Sample Data
    4. Demo - Creating an Analysis using Your Own Amazon S3 Data
    5. Visual Types
    6. Stories
    7. Big Data Visualization
    8. Key Takeaways
  8. Chapter 8 : Big Data on AWS - Security
    1. Learning Objective
    2. EMR Security and Security Group
    3. Roles and Private Subnet
    4. Encryption at Rest and In-Transit
    5. Redshift Security
    6. Encryption at Rest using CloudHSM
    7. Cloud HSM versus AWS KMS
    8. Limit Data Access
    9. Key Takeaways

Product information

  • Title: AWS Certified Big Data - Specialty Certification
  • Author(s): Learnkart Technology Private Limited
  • Release date: August 2020
  • Publisher(s): Packt Publishing
  • ISBN: 9781800563773