Data Warehouse Migration to Amazon Redshift — Part 2

1. Getting Started with Amazon Redshift (AR)

  • Setup an AWS account
  • Sign up and get started from the Amazon Redshift detail page or via the AWS Management Console
  • Install SQL Client Drivers and Tools
  • Configure Firewall Rules
  • Create a Redshift Cluster
  • Create a database schema based on your requirement in the cluster
  • Use an ETL framework to populate the Data warehouse
  • EC2 Classic subnet
  • VPC subnet

2. Pros of using Amazon Redshift

  • Analyze more data
  • Faster time to market
  • Get better insights
  • Match capacity with Demand
  1. Transition from unsustainable painful operations to efficient cost effective cluster, squeak-free operations, and grab a sizeable reduction of costs. Migration to Redshift from on-premise platform is made possible at a fraction of the cost.
  2. Single source of truth — Organizations that have high data volumes require a unified and organized Database to handle not only the volume but also act as a source of truth which makes Redshift as the best solution provider.
  3. Fast — You can run aggregations on hundreds of millions of rows in a few seconds. Very fast query performance due to columnar-storage databases that leverage the Massively Parallel Processing (MPP) capabilities of its data warehouse architecture. Petabyte-scale data warehouse, without any loss in performance and low cost:
  • Parallel and Distributed Processing
  • Less I/O Storage
  • Hardware is optimized for I/O intensive workloads
  • Enhanced Networking
  • Regular movement of auto fixed enhancements
  1. Economical
  • Easy and Straightforward Pricing
  • Leader nodes are not charged
  • There are no upfront costs
  1. Complete governance and control
  • Ceaseless/progressive backup of your data to Amazon S3 and across regions
  • Streaming restore
  1. Fault Tolerance
  2. Built-in Security
  • Data Load is encoded from Amazon S3
  • Data in progress is secured by SSL enabled connections
  • Amazon VPC allows only connections made from inside the network thus making network isolation possible
  • Audit trailing to keep track of the transaction history. You can make use of AWS Cloud Trail to record the account activities
  1. Vigorous
  • Authorizes user-defined functions
  • Uses Machine Learning and Data Science
  1. Service Oriented Architecture (SOA)
  2. Business Tools such as Tableau is supported
  3. Supports all the data warehouse core features such as SCD1 and SCD2, and different schemas like the star schema
  4. Set up a Disaster Recovery (DR) environment with a few clicks in the AR Management Console. Allows you to keep copies of your backups in multiple AWS regions and in the case of a service interruption in one AWS region, you can restore your cluster from the backup in a different AWS region, and gain read/write access to your cluster within a few minutes of initiating the restoring operation

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Developer and Designer

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Abhikhya Ashi

Abhikhya Ashi

Developer and Designer

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