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Data Engineering on AWS – The complete training

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Build your confidence and credibility as data engineer, data architect, and other data-related roles on AWS Cloud


1. Introduction - Data is the new oil
  • 1. Introduction

  • 2. Know your trainer
  • 1. Know your trainer

  • 3. Getting started with Data Analytics
  • 1.1 03a Data Engineering on AWS.pdf
  • 1. Data Engineering on AWS
  • 2.1 003b - Basic Terminologies.pdf
  • 2. Basic Terminologies

  • 4. AWS Glue - Catalog and process your data
  • 1.1 04 -AWS Glue - Catalog and process your data.pdf
  • 1.2 Customers and sales csv.zip
  • 1. Glue Data Catalog
  • 2. Glue ETL - Part 1
  • 3. ETL Job - Part 2
  • 4. ETL Job - Part 3
  • 5. Workflows
  • 6. Job Bookmark
  • 7. Execution Type
  • 8. Data Quality - Part 1
  • 9. Data Quality - Part 2
  • 10. Glue Databrew
  • 11. Additional Features

  • 5. Amazon Redshift - A data warehouse in AWS
  • 1.1 005 - Amazon Redshift - A data warehouse in AWS.pdf
  • 1. Amazon Redshift
  • 2. Architecture
  • 3. Creating a cluster
  • 4. Query Editor v2
  • 5. Distribution styles
  • 6. Cluster operations
  • 7. Data API
  • 8. Redshift Spectrum
  • 9. Redshift Serverless - Part 1
  • 10. Redshift Serverless - Part 2
  • 11. Materialized views
  • 12. WLM and concurrency
  • 13. Datashare
  • 14. Additional information

  • 6. Processing Streaming Data on Amazon Kinesis and Amazon MSK
  • 1.1 006 - Processing Streaming Data on Amazon Kinesis and Amazon MSK.pdf
  • 1. What is Streaming Data
  • 2. Streaming Services in AWS
  • 3. Amazon Kinesis family
  • 4. Amazon Kinesis Data Streams
  • 5. Capacity Mode
  • 6. Shard Iterators
  • 7. Kinesis Data Generator
  • 8. Data Stream Porducers
  • 9. Data Stream Consumer
  • 10. Enhanced fan-out
  • 11. Amazon Kinesis Firehose
  • 12. Dynamic Partitioning
  • 13. Data Stream vs. Data Firehose
  • 14. Managed Service for Apache Flink
  • 15. Flink Application
  • 16. Flink Studio
  • 17. Apache Kafka
  • 18. Amazon Managed Service for Kafka
  • 19. MSK Cluster
  • 20. Kafka Topic
  • 21. Send and receive messages
  • 22. Amazon MSK Serverless
  • 23. MSK Provisioned vs. Serverless
  • 24. Amazon MSK Connect
  • 25. Amazon Kinesis vs. Amazon MSK

  • 7. Running Big data workloads on Amazon EMR
  • 1.1 007 Running Big data workloads on Amazon EMR.pdf
  • 1. What is Big data
  • 2. Map Reduce
  • 3. Big data ecosystem
  • 4. Amazon EMR
  • 5. Storage for EMR
  • 6. Creating EMR cluster - Part 1
  • 7. Creating EMR cluster - Part 2
  • 8. Migration
  • 9. Amazon EMR Serverless
  • 10. Cost optimization

  • 8. Building Datalakes on AWS
  • 1.1 008 - Building Datalakes on AWS.pdf
  • 1. What is Datalake
  • 2. Data warehouse vs. Datalake
  • 3. AWS Lake Formation
  • 4. How it works
  • 5. Setting up a Datalake - Part 1
  • 6. Setting up a Datalake - Part 2
  • 7. Datalake permissions
  • 8. Tag based permissions
  • 9. Open Table Formats

  • 9. Query your data using Amazon Athena
  • 1.1 009 - Query your data using Amazon Athena.pdf
  • 1. Why to use Amazon Athena
  • 2. How it works
  • 3. Optimizing queries in Athena - Part 1
  • 4. Optimizing queries in Athena - Part 2
  • 5. Workgroups
  • 6. Federated query - Part 1
  • 7. Federated query - Part 2

  • 10. Visualize your data using Amazon Quicksight
  • 1.1 0010 - Visualize your data using Amazon Quicksight.pdf
  • 1. Data visualization
  • 2. Getting started
  • 3. Integration with Amazon Athena

  • 11. Orchestrating your data pipeline
  • 1.1 011 - Orchestrating your data pipeline.pdf
  • 1. Orchestrating your data pipeline
  • 2. Which one to choose
  • 3. Amazon AppFlow
  • 4. AWS Data Exchange
  • 5. AWS Step Functions - Part 1
  • 6. AWS Step Functions - Part 2
  • 7. AWS Step Functions - Part 3

  • 12. Data Migration services in AWS
  • 1. A note before you proceed
  • 2.1 012 -Data Migration services in AWS.pdf
  • 2. Migrating your databases to AWS
  • 3. AWS DMS - Part 1
  • 4. AWS DMS - Part 2
  • 5. AWS DMS - Part 3
  • 6. Migrating your data to AWS
  • 7. AWS DataSync - Part 1
  • 8. AWS DataSync - Part 2
  • 9. AWS Transfer Family - Part 1
  • 10. AWS Transfer Family - Part 2
  • 11. AWS Snow Family

  • 13. Going beyond AWS analytics services
  • 1. A note before you proceed
  • 2.1 013 - Going beyond AWS analytics services.pdf
  • 2. AWS Lambda - Important features
  • 3. AWS Lambda - Concurrency
  • 4. AWS Lambda - Layers
  • 5. AWS Lambda - VPC connectivity
  • 6. AWS Lambda - Permissions
  • 7. Amazon S3 - Encryption
  • 8. Amazon S3 - Glacier Storage Tiers
  • 9. Amazon S3 - Events Notification
  • 10. Amazon S3 - Lifecycle policies
  • 11. Amazon S3 - Intelligent Tier
  • 12. Amazon S3 - Select
  • 13. Amazon S3 - Object Lambda
  • 14. Amazon EC2 - EBS volumes
  • 15. Amazon RDS - Performance insights
  • 16. Amazon DynamoDB - Streams
  • 17. Amazon DynamoDB - Global tables
  • 18. Amazon DynamoDB - Auto Scaling

  • 14. Final note
  • 1. Final note
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