Amazon Redshift Course

 

Amazon Redshift Course Overview

Amazon Redshift is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake. Redshift delivers ten times faster performance than other data warehouses by using machine learning, massively parallel query execution, and columnar storage on high-performance disk. You can setup and deploy a new data warehouse in minutes, and run queries across petabytes of data in your Redshift data warehouse, and Exabyte of data in your data built on Amazon S3.

You will begin with introduction to the course, realizing what an information data warehouse is, the advantages of Redshift, and how Redshift thinks about to different tools. From that point including data loading, data distribution and fundamental Redshift use. In this course we start from the basic AWS storage service S3 and explore multiple option before going deep in to redshift. The course starts with overview of AWS and related Big Data services.

Amazon Redshift is an Internet hosting service and data warehouse product which forms part of the larger cloud-computing platform Amazon Web Services.

This course is designed for the absolute beginner, developers, database analysts anyone interested to change career into Amazon Redshift.

There are no pre-requisites for taking this course.  Anyone can take the course.

After completion of the course, you will get an opportunity as Amazon Data engineer, Data consultant, Developer in Mind tree, Capgemini, Amazon, Accenture, CDM smith, Sony and more.

These topics covered in the course: Data Warehousing on AWS, Introduction to AWS Redshift, Redshift Architecture Overview, Redshift Fundamentals, Monitoring cluster performance, Unloading Data, Performance Tuning and more.

Amazon Redshift Course Syllabus

Introduction

  • Introduction to the Course
  • Getting started, what you’ll need.
  • AWS A Look from Top Overview
  • The history of AWS so far
  • AWS – Overview

Data Warehousing on AWS

  • Need for Data Warehousing
  • What Is A Data Warehouse?
  • Shortcomings Of Self-Owned Data Warehouses
  • Benefits Of A Public Cloud Data Warehouse
  • Benefits Of Redshift
  • How Companies Use Redshift
  • Third Party Visualization Tools Overview
  • How Redshift Compares To Other Analytics Tools

Introduction to AWS Redshift

  • AWS Redshift- Data Warehouse-as-a-Service
  • Features
  • Pricing
  • AWS Management Console Walkthrough

Redshift Architecture Overview

  • Architecture
  • Clusters
  • Leader and Compute Nodes
  • Node Slices
  • Columnar Storage for performance
  • Economics of Redshift
  • Key differentiators
  • Common use cases

Redshift Fundamentals

  • Redshift Basics
  • Data Loading
  • Data Distribution Concepts
  • Basic Redshift Usage
  • Creating An AWS Account (Lab)
  • Creating A Redshift Cluster (Lab)
  • Configuring SQL Workbench (Lab)
  • Loading Data Into S3 (Lab)
  • Loading Data Into A Redshift Cluster (Lab)
  • Querying A Redshift Cluster (Lab)

Monitoring cluster performance

  • Analyzing Cluster performance data
  • Analyzing query execution
  • Creating Alarm and working with performance metrics

Unloading Data

  • Unloading Data to Amazon S3
  • Unloading Encrypted Data Files
  • Unloading Data in Delimited or Fixed-Width Format
  • Reloading unloaded data

Performance Tuning

  • Query Processing
  • Query Planning &Execution
  • Query Analysis Workflow
  • Query Performance Tuning –S1
  • Workload Management
  • Query Queues and Concurrency
  • WLM Configuration
  • WLM Queue Rules
  • Dynamic and Static Properties
  • Monitoring Workload Management
  • Query Performance Tuning – S2
  • Troubleshooting Queries
  • Admin queries to analyze performance

Redshift Advance

  • Best Practices for Designing Tables
  • Best Practices Data Loading S1
  • Best Practices Data Loading S2
  • Unload query result
  • JSON Support
  • Loading data from EMR Cluster
  • User Defined Functions
  • Queries Troubleshooting
  • Timed Queries
  • Migration of Existing BI Systems to Redshift
  • Cross Region Data Copying
  • Data Loading from OLTP databases to Redshift and Limitations
  • ETL and ELT on Redshift
  • BI tools integration and limitation in Redshift
  • Designing Data warehouse