Mastering Amazon Redshift and Serverless for Data Engineers

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Durga Viswanatha Raju Gadiraju,Naga Bhuwaneshwar,Kavitha Penmetsa

5:46:30

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1. Getting Started with Amazon Redshift

1. Getting Started with Amazon Redshift - Introduction.mp4

00:56

2. Create Redshift Cluster using Free Trial.mp4

03:34

3. Connecting to Database using Redshift Query Editor.mp4

03:33

4. Get list of tables querying information schema.mp4

03:34

5. Run Queries against Redshift Tables using Query Editor.mp4

03:37

6. Create Redshift Table using Primary Key.mp4

03:35

7. Insert Data into Redshift Tables.mp4

07:17

8. Update Data in Redshift Tables.mp4

05:13

9. Delete data from Redshift tables.mp4

04:17

10. Redshift Saved Queries using Query Editor.mp4

03:40

11. Deleting Redshift Cluster.mp4

02:37

12. Restore Redshift Cluster from Snapshot.mp4

04:48

2. Copy Data from s3 into Redshift Tables

1. Copy Data from s3 to Redshift - Introduction.mp4

01:27

2. Setup Data in s3 for Redshift Copy.mp4

04:55

3. Create Database and Table for Redshift Copy Command.mp4

03:33

4. Create IAM User with full access on s3 for Redshift Copy.mp4

03:37

5. Run Copy Command to copy data from s3 to Redshift Table.mp4

03:15

6. Troubleshoot Errors related to Redshift Copy Command.mp4

02:17

7. Run Copy Command to copy from s3 to Redshift table.mp4

02:12

8. Validate using queries against Redshift Table.mp4

02:44

9. Overview of Redshift Copy Command.mp4

05:26

10. Create IAM Role for Redshift to access s3.mp4

04:49

11. Copy Data from s3 to Redshift table using IAM Role.mp4

06:05

12. Setup JSON Dataset in s3 for Redshift Copy Command.mp4

03:59

13. Copy JSON Data from s3 to Redshift table using IAM Role.mp4

03:57

3. Develop Python Applications using Redshift Cluster

1. Develop application using Redshift Cluster - Introduction.mp4

00:59

2. Allocate Elastic Ip for Redshift Cluster.mp4

03:46

3. Enable Public Accessibility for Redshift Cluster.mp4

04:01

4. Update Inbound Rules in Security Group to access Redshift Cluster.mp4

05:16

5. Create Database and User in Redshift Cluster.mp4

04:57

6. Connect to database in Redshift using psql.mp4

03:47

7. Change Owner on Redshift Tables.mp4

03:06

8. Download Redshift JDBC Jar file.mp4

01:51

9. Connect to Redshift Databases using IDEs such as SQL Workbench.mp4

04:30

10. Setup Python Virtual Environment for Redshift.mp4

04:45

11. Run Simple Query against Redshift Database Table using Python.mp4

06:30

12. Truncate Redshift Table using Python.mp4

03:56

13. Create IAM User to copy from s3 to Redshift Tables.mp4

02:23

14. Validate Access of IAM User using Boto3.mp4

04:51

15. Run Redshift Copy Command using Python.mp4

06:31

4. Redshift Tables with Distkeys and Sortkeys

1. Redshift Tables with Distkeys and Sortkeys - Introduction.mp4

03:58

2. Quick Review of Redshift Architecture.mp4

03:34

3. Create multi-node Redshift Cluster.mp4

04:34

4. Connect to Redshift Cluster using Query Editor.mp4

02:47

5. Create Redshift Database.mp4

01:34

6. Create Redshift Database User.mp4

03:46

7. Create Redshift Database Schema.mp4

05:37

8. Default Distribution Style of Redshift Table.mp4

04:14

9. Grant Select Permissions on Catalog to Redshift Database User.mp4

03:22

10. Update Search Path to query Redshift system tables.mp4

07:09

11. Validate table with DISTSTYLE AUTO.mp4

06:27

12. Create Cluster from Snapshot to the original state.mp4

06:59

13. Overview of Node Slices in Redshift Cluster.mp4

03:39

14. Overview of Distribution Styles.mp4

03:48

15. Distribution Strategies for retail tables in Redshift.mp4

02:17

16. Create Redshift tables with distribution style all.mp4

05:50

17. Troubleshoot and Fix Load or Copy Errors.mp4

04:03

18. Create Redshift Table with Distribution Style Auto.mp4

03:49

19. Create Redshift Tables using Distribution Style Key.mp4

07:50

20. Delete Cluster with manual snapshot.mp4

01:27

5. Redshift Federated Queries and Spectrum

1. Redshift Federated Queries and Spectrum - Introduction.mp4

01:28

2. Overview of integrating RDS and Redshift for Federated Queries.mp4

05:30

3. Create IAM Role for Redshift Cluster.mp4

02:26

4. Setup Postgres Database Server for Redshift Federated Queries.mp4

07:27

5. Create tables in Postgres Database for Redshift Federated Queries.mp4

06:02

6. Creating Secret using Secrets Manager for Postgres Database.mp4

04:05

7. Accessing Secret Details using Python Boto3.mp4

06:47

8. Reading Json Data to Dataframe using Pandas.mp4

08:51

9. Write JSON Data to Database Tables using Pandas.mp4

10:43

10. Create IAM Policy for Secret and associate with Redshift Role.mp4

04:45

11. Create Redshift Cluster using IAM Role with permissions on secret.mp4

05:01

12. Create Redshift External Schema to Postgres Database.mp4

06:00

13. Update Redshift Cluster Network Settings for Federated Queries.mp4

09:43

14. Performing ETL using Redshift Federated Queries.mp4

04:46

15. Clean up resources added for Redshift Federated Queries.mp4

03:09

16. Grant Access on Glue Data Catalog to Redshift Cluster for Spectrum.mp4

03:51

17. Setup Redshift Clusters to run queries using Spectrum.mp4

02:33

18. Quick Recap of Glue Catalog Database and Tables for Redshift Spectrum.mp4

02:25

19. Create External Schema using Redshift Spectrum.mp4

03:21

20. Run Queries using Redshift Spectrum.mp4

03:37

21. Cleanup the Redshift Cluster.mp4

01:10

Description

In-Depth Course on Amazon Redshift, Redshift Serverless, Integration with EMR, AWS Step Functions, AWS Lambda and more

What You'll Learn?

Getting Started with Amazon Redshift using AWS Web Console
Copy Data from s3 into AWS Redshift Tables using Redshift Queries or Commands
Develop Applications using Redshift Cluster using Python as Programming Language
Copy Data from s3 into AWS Redshift Tables using Python as Programming Language
Create Tables using Databases setup on AWS Redshift Database Server using Distribution Keys and Sort Keys
Run AWS Redshift Federated Queries connecting to traditional RDBMS Databases such as Postgres
Perform ETL using AWS Redshift Federated Queries using Redshift Capacity
Integration of AWS Redshift and AWS Glue Catalog to run queries using Redshift Spectrum
Run AWS Redshift Spectrum Queries using Glue Catalog Tables on Datalake setup using AWS s3
Getting Started with Amazon Redshift Serverless by creating Workgroup and Namespace
Integration of AWS EMR Cluster with Amazon Redshift using Serverless Workgroup
Develop and Deploy Spark Application on AWS EMR Cluster where the processed data will be loaded into Amazon Redshift Serverless Workgroup

Who is this for?

University Students who want to learn AWS Redshift for Data Warehousing

Aspiring Data Engineers and Data Scientists who want to learn about AWS Redshift for Data Warehousing

Experienced Application Developers who would like to explore AWS Redshift for Data Warehousing

Experienced Data Engineers to build end to end data pipelines using Python around Data Marts created using AWS Redshift

Any IT Professional who is keen to deep dive into AWS Redshift for Data Warehousing on AWS

What You Need to Know?

A computer science or IT Degree or 1 or 2 years of IT Experience

Ability to write SQL Queries using any Relational or Data Warehouse or MPP Database

Basic Linux Skills with ability to run commands using Terminal

Basic Programming using Python is desired even though it is mandatory for most part of the course

More details

Description
AWS or Amazon RedshiftÂ is one of the key AWS Services used in building Data Warehouses or Data Marts to serve reports and dashboards for business users. As part of this course, you will end up learning AWSÂ or Amazon RedshiftÂ by going through all the important features of AWSÂ or Amazon Redshift to build Data Warehouses or Data Marts.
We have covered features such as Federated Queries, Redshift Spectrum, Integration with Python, AWSÂ Lambda Functions, Integration of Redshift with EMR, and End-to-End Pipeline using AWS Step Functions.
Here is the detailed outline of the course.
First, we will understand how to Get Started with Amazon Redshift using AWSÂ Web Console. We will see how to create a cluster, how to connect to the cluster, and also how to run the queries using a Web-based query editor. We will also go ahead and create a Database and tables in the Redshift Cluster. Once we set up a Database and tables, we will also go through the details related to CRUD Operations against tables in Databases in Redshift Cluster.
Once we have the databases and tables in Redshift Cluster, it is time for us to understand how to get data into the tables in Redshift Cluster. One of the common approaches we use to get data into the Redshift cluster is by Copying Data from s3 into Redshift Tables. We will go through the step-by-step process of copying the data into Redshift tables from s3 using the copy command.
Python is one of the prominent programming languages to build Data Engineering or ETLÂ Applications. It is extensively used to build ETLÂ Jobs to get data into Database Tables in Redshift Cluster. Once we understand how to get data from s3 to Redshift tables using Copy Command, we will learn how to Develop Python-based Data Engineering or ETL Applications using Redshift Cluster. We will learn how to perform CRUDÂ operations and also how to take run COPY Commands using Python-based programs.
Once we understand how to build applications using Redshift Cluster, we will go through some of the key concepts used while creating Redshift Tables with Distkeys and Sortkeys.
We can also connect to remote databases such as Postgres and run queries directly on the remote database tables using Redshift Federated Queries and also we can run queries on top of Glue or Athena Catalog using Redshift Spectrum. You will learn how to leverage Redshift Federated Queries and Spectrum to process data in remote Database tables or s3 without copying the data.
You will also get an overview of Amazon Redshift Serverless as part of Getting Started with Amazon Redshift Serverless.
Once you learn Amazon Redshift Serverless, you will end up deploying a Pipeline where a Spark Application is deployed on AWS EMRÂ Cluster which will load the data processed by Spark into Redshift.
Who this course is for:
University Students who want to learn AWS Redshift for Data Warehousing
Aspiring Data Engineers and Data Scientists who want to learn about AWS Redshift for Data Warehousing
Experienced Application Developers who would like to explore AWS Redshift for Data Warehousing
Experienced Data Engineers to build end to end data pipelines using Python around Data Marts created using AWS Redshift
Any IT Professional who is keen to deep dive into AWS Redshift for Data Warehousing on AWS

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Data Science

Durga Viswanatha Raju Gadiraju

Instructor's Courses

20+ years of experience in executing complex projects using a vast array of technologies including Big Data and the Cloud.ITVersity, Inc. - is a US-based organization that provides quality training for IT professionals and we have a track record of training hundreds of thousands of professionals globally.Building an IT career for people with required tools such as high-quality material, labs, live support, etc to upskill and cross-skill is paramount for our organization.At this time our training offerings are focused on the following areas:* Application Development using Python and SQL* Big Data and Business Intelligence* Cloud* Datawarehousing, Databases

Naga Bhuwaneshwar

Instructor's Courses

Kavitha Penmetsa

Instructor's Courses

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