RKSOFT is a Best of Best Amazon Redshift Training institute providing customer project-based Training and Placements assurance in Hyderabad.
Amazon Redshift is a data warehouse service that makes it simple to efficiently analyse all your data using your existing business intelligence tools.
Redshift Course Content:-
Introduction to Amazon Web services
Ø Amazon Web Services Stack
Ø Introduction to Amazon DATABASE
Introduction to AWS Redshift
Ø AWS Redshift – Data Warehouse-as-a-Service
Walkthrough the AWS Management Console. – Hands On
Redshift Architecture Overview
Ø Leader and Compute Nodes
Ø Node Slices
Ø Columnar Storage for performance
Ø Economics of Redshift
Ø Key differentiators
Ø Common Use cases
Up and Running with AWS Redshift – Hands On
Ø Launch a new Redshift Cluster
Ø Modifying a Cluster – resize, showdown, delete, reboot.
Ø Security Groups.
Ø Parameter groups.
Ø Database Encryption.
Ø Backup and recovery – creating manual snapshot and automatic snapshots.
Ø Authorize access to Cluster
Ø Getting Information about Cluster Configuration.
Ø Database Audit Logging
Accessing Amazon Redshift cluster – Hands On
Ø JDBC and ODBC interfaces
Ø Install and configure client SQL tools using JDBC and/or ODBC drivers
Ø Create Database, Users, user groups, permissions and access controls.
Ø Connect to Redshift Cluster
Ø Load sample data into cluster
Ø Create and test queries against the data
Monitor cluster performance – Hands On
Ø Analyzing cluster Performance data
Ø Analyze query execution
Ø Creating Alarm and working with performance metrics
Designing tables – Deep dive – Hands On
Ø DDL SQL – Creating Tables, Alter tables, Drop tables.
Ø LIMITATIONS and what is implemented differently.
Ø Selecting distribution Style and distribution keys.
Ø Selecting Sort Key.
Ø Choose best Distribution key covering various use cases
Ø Choosing best sort keys covering various use cases.
Ø Choosing a column compression type.
Ø Define constraints
Loading data – Deep Dive – Hands On
Ø Using Copy to Load data
Ø Loading data from S3
Ø Using a Manifest to Specify Data Files
Ø Loading Compressed Files
Ø Loading Fixed-Width Data
Ø Loading Multi-byte Data
Ø Loading Encrypted Data Files
Ø Loading from JSON files.
Ø Insert, Select, Update, Delete
Ø Deep Copy
Ø LIMITATIONS Troubleshooting
Ø S3ServiceException Errors
Ø System Tables for Troubleshooting Data Loads
Ø Multi-byte Character Load Errors
Ø Error Reference
Ø Unloading Data to Amazon S3
Ø Unloading Encrypted Data Files
Ø Unloading Data in Delimited or Fixed-Width Format
Ø Reloading Unloaded Data
Performance Tuning – Hands On
Ø Query Processing
Ø Query Planning And Execution Workflow
Ø Reviewing Query Plan Steps
Ø Query Plan
Ø Factors Affecting Query Performance
Ø Analyzing and Improving Queries
Ø Query Analysis Workflow
Ø Reviewing Query Alerts
Ø Analyzing the Query Plan
Ø Analyzing the Query Summary
Ø Improving Query Performance
Ø Diagnostic Queries for Query Tuning
Ø Implementing Workload Management
Ø Defining Query Queues
Ø Modifying the WLM Configuration
Ø WLM Queue Assignment Rules
Ø Assigning Queries to Queues
Ø Dynamic and Static Properties
Ø Monitoring Workload Management
Ø Configuring WLM Queues to Improve Query Processing
Ø Troubleshooting Queries
Ø Building Admin queries from system tables to analyze performance.
Ø Migration of Existing BI Systems to Redshift
Ø Data Loading from OLTP databases to Redshift and Limitations.
Ø ETL and ELT on Redshift.
Ø Limitations from industry standard Integration and BI tools w.r.t Redshift.
Ø Build custom ETL and/or ELT framework from an OLTP db to Redshift
Ø Use Powershell /Python AWS SDK’s for loading data from SQL Server/ORACLE/Postgres to Redshift through S3.
Ø Limitations and Best Practices for Redshift Data warehouse implementation.