Data Engineering on AWS

Data Engineering on AWS

• Lesson 01: Introduction: Data Is the New Oil

  08:10Preview

  • 1.01 Introduction

    08:10

• Lesson 02: Know Your Trainer

  03:01Preview

  • 2.01 Know Your Trainer

    03:01

• Lesson 03: Getting Started with Data Analytics

  24:01Preview

  • 3.01 Data Engineering on AWS

    12:47

  • 3.02 Basic Terminologies

    11:14

• Lesson 04: AWS Glue: Catalog and Process Your Data

  02:31:53Preview

  • 4.01 Glue Data Catalog

    31:31

  • 4.02 Glue ETL: Part 1

    04:10

  • 4.03 Glue ETL: Part 2

    09:31

  • 4.04 Glue ETL: Part 3

    22:14

  • 4.05 Workflows

    12:09

  • 4.06 Job Bookmark

    05:00

  • 4.07 Execution Type

    09:54

  • 4.08 Data Quality: Part 1

    04:45

  • 4.09 Data Quality: Part 2

    21:51

  • 4.10 Glue DataBrew

    21:28

  • 4.11 Additional Features

    09:20

• Lesson 05: Amazon Redshift: A Data Warehouse in AWS

  02:33:34Preview

  • 5.01 Amazon Redshift

    08:55

  • 5.02 Architecture

    10:47

  • 5.03 Creating a Cluster

    16:36

  • 5.04 Query Editor v2

    08:48

  • 5.05 Distribution Styles

    16:06

  • 5.06 Cluster Operations

    05:22

  • 5.07 Data API

    06:44

  • 5.08 Redshift Spectrum

    20:42

  • 5.09 Redshift Serverless: Part 1

    12:49

  • 5.10 Redshift Serverless: Part 2

    08:01

  • 5.11 Materialized Views

    09:40

  • 5.12 WLM and Concurrency

    09:52

  • 5.13 DataShare

    08:18

  • 5.14 Additional Information

    10:54

• Lesson 06: Processing Streaming Data on Amazon Kinesis and Amazon MSK

  03:26:55Preview

  • 6.01 What Is Streaming Data?

    08:29

  • 6.02 Streaming Services in AWS

    05:43

  • 6.03 Amazon Kinesis Family

    02:32

  • 6.04 Amazon Kinesis Data Streams

    13:14

  • 6.05 Capacity Mode

    07:07

  • 6.06 Shard Iterators

    13:00

  • 6.07 Kinesis Data Generator

    07:00

  • 6.08 Data Stream Producers

    04:11

  • 6.09 Data Stream Consumer

    02:51

  • 6.10 Enhanced Fan-Out

    05:50

  • 6.11 Amazon Kinesis Firehose

    18:45

  • 6.12 Dynamic Partitioning

    09:19

  • 6.13 Data Stream vs. Data Firehose

    04:46

  • 6.14 Managed Service for Apache Flink

    11:17

  • 6.15 Flink Application

    15:23

  • 6.16 Flink Studio

    03:44

  • 6.17 Apache Kafka

    09:47

  • 6.18 Amazon Managed Service for Kafka

    08:57

  • 6.19 MSK Cluster

    09:54

  • 6.20 Kafka Topic

    21:54

  • 6.21 Send and Receive Messages

    05:24

  • 6.22 Amazon MSK Serverless

    05:27

  • 6.23 MSK Provisioned vs Serverless

    02:37

  • 6.24 Amazon MSK Connect

    04:00

  • 6.25 MSK Provisioned vs. Serverless

    05:44

• Lesson 07: Running Big Data Workloads on Amazon EMR

  01:11:20Preview

  • 7.01 What Is Big Data?

    03:31

  • 7.02 MapReduce

    05:19

  • 7.03 Big Data Ecosystem

    04:41

  • 7.04 Amazon EMR

    07:56

  • 7.05 Storage for EMR

    07:28

  • 7.06 Creating EMR Cluster: Part 1

    16:15

  • 7.07 Creating EMR Cluster: Part 2

    08:59

  • 7.08 Migration

    09:12

  • 7.09 Amazon EMR Serverless

    04:09

  • 7.10 Cost Optimization

    03:50

• Lesson 08: Building Data Lakes on AWS

  01:24:45Preview

  • 8.01 What Is a Data Lake?

    08:35

  • 8.02 Data Warehouse vs. Data Lake

    07:08

  • 8.03 AWS Lake Formation

    08:46

  • 8.04 How It Works?

    10:00

  • 8.05 Setting Up a Data Lake: Part 1

    17:43

  • 8.06 Setting Up a Data Lake: Part 2

    07:16

  • 8.07 Data Lake Permissions

    13:29

  • 8.08 Tag-Based Permissions

    08:35

  • 8.09 Open Table Formats

    03:13

• Lesson 09: Query Your Data Using Amazon Athena

  01:27:32Preview

  • 9.01 Why Use Amazon Athena?

    06:51

  • 9.02 How It Works?

    13:38

  • 9.03 Optimizing Queries in Athena: Part 1

    15:35

  • 9.04 Optimizing Queries in Athena: Part 2

    13:03

  • 9.05 Workgroups

    13:30

  • 9.06 Federated Query: Part 1

    05:17

  • 9.07 Federated Query: Part 2

    19:38

• Lesson 10: Visualize Your Data Using Amazon QuickSight

  37:58Preview

  • 10.01 Data Visualization

    07:13

  • 10.02 Getting Started

    18:44

  • 10.03 Integration with Amazon Athena

    12:01

• Lesson 11: Orchestrating Your Data Pipeline

  49:01Preview

  • 11.01 Orchestrating Your Data Pipeline

    09:20

  • 11.02 Which One to Choose?

    05:47

  • 11.03 Amazon AppFlow

    07:36

  • 11.04 AWS Data Exchange

    06:31

  • 11.05 AWS Step Functions: Part 1

    06:17

  • 11.06 AWS Step Functions: Part 2

    07:43

  • 11.07 AWS Step Functions: Part 3

    05:47

• Lesson 12: Data Migration Services in AWS

  02:22:46Preview

  • 12.01 A Note Before You Proceed

    01:42

  • 12.02 Migrating Your Databases to AWS

    18:04

  • 12.03 AWS DMS: Part 1

    10:46

  • 12.04 AWS DMS: Part 2

    23:11

  • 12.05 AWS DMS: Part 3

    07:19

  • 12.06 Migrating Your Data to AWS

    04:05

  • 12.07 AWS DataSync: Part 1

    08:00

  • 12.08 AWS DataSync: Part 2

    23:54

  • 12.09 AWS Transfer Family: Part 1

    10:24

  • 12.10 AWS Transfer Family: Part 2

    17:23

  • 12.11 AWS Snow Family

    17:58

• Lesson 13: Going Beyond AWS Analytics Services

  01:53:34Preview

  • 13.01 A Note Before You Proceed

    02:09

  • 13.02 AWS Lambda: Important Features

    05:04

  • 13.03 AWS Lambda: Concurrency

    07:11

  • 13.04 AWS Lambda: Layers

    05:55

  • 13.05 AWS Lambda: VPC Connectivity

    05:16

  • 13.06 AWS Lambda: Permissions

    04:43

  • 13.07 Amazon S3: Encryption

    05:17

  • 13.08 Amazon S3: Glacier Storage Tiers

    03:07

  • 13.09 Amazon S3: Events Notification

    03:39

  • 13.10 Amazon S3: Lifecycle Policies

    09:18

  • 13.11 Amazon S3: Intelligent Tier

    27:17

  • 13.12 Amazon S3: Select

    05:18

  • 13.13 Amazon S3: Object Lambda

    08:50

  • 13.14 Amazon EC2: EBS Volumes

    05:38

  • 13.15 Amazon RDS: Performance Insights

    02:42

  • 13.16 Amazon DynamoDB: Streams

    05:03

  • 13.17 Amazon DynamoDB: Global Tables

    04:04

  • 13.18 Amazon DynamoDB: Auto Scaling

    03:03

• Lesson 14: Final Note

  00:34Preview

  • 14.01 Final Note

    00:34