Enterprise AI Platform on Kubernetes

Introduction to AWS Platform

Amazon Redshift is a type of data warehouse service in the Cloud which is fully managed, reliable, scalable and fast and is a part of Amazon’s Cloud Computing the platform, which is Amazon Web Services. We can start with some gigabytes of data only and scale it up to petabytes or more.
The first thing we have to do to create it is to launch a set of nodes, also known as the Amazon Redshift cluster. After setting up the clusters, we can upload the data set and after that perform the data analysis queries on it.

Amazon QuickSight is a type of business analytics cloud-based service which can be used to build visualizations, perform ad hoc analysis(ad hoc is an adjective used to describe things that are created on the spot and generally for single use only), and Get business insights from the data. Amazon QuickSight can read the data from any of the AWS sources, whether it is Amazon Redshift or Amazon Aurora or Relational Database Service or from Amazon S3.


Why Choose Amazon Redshift?

When the queries started taking a long time for execution or an organization is looking for a better way for running the analytic query against the on growing data, then it must choose a data warehouse. Some of the reasons due to which Amazon Redshift is considered as a best data warehouse for executing the analytic query and executing query fastly and efficiently are as follows –

Ease of Configuration and Management When it comes to setup and management, Amazon Redshift provides significant efficiency and performance to daily workflow. Once the schemas and definitions are set, Amazon Redshift manages all the provisioning, configuration, and patching. In this durability and availability of data is also assured as the data back up of data is done with the help of Amazon S3.

Provides Fast Scaling with a Few Complications – As Redshift is a cloud-based structure, which is directly hosted on the Amazon Web Services. So it is one of the most significant benefits that provide Redshift a flexible architecture that can scale up in some seconds only and can meet the changing storage demands.

Redshift can be easily scaled up or down by quickly activating the individual nodes of varying size. This feature of Redshift is very much useful for smaller organizations which experience significant growth and have to scale their existing solutions.

Keeps Cost Relatively Low – Compared to other data warehouses, Redshift provides a lot of both entry-level affordability and massive cost efficiency at scale. Amazon Redshift’s columnar based architecture for query optimizations reduces the input/output load to return the result in some seconds and also improves the cost.

Offers significant Query Speed Upgrades – While executing larger data sets on other data warehouses, queries experience a lag in speed. However, executing queries on Redshift gives the result faster even while executing on petabytes of data. Amazon’s massively parallel processing lets the business intelligence tools with the redshift connector and processes several queries across multiple nodes simultaneously while reducing workloads, due to which the speed will be Increased.

Gives the Strong or Robust Security Tools – Larger data sets generally contain sensitive data, so security is the major part of the concern for a data warehouse. So, the Redshift provides a few different encryption and security tools that protects the warehouse efficiently. Redshift includes SSL encryption for data and when talking about AWS S3 Server, they offer the encryption for both the client as well as server side. It also includes a VPC for network isolation as well as different access control tools.


Why Amazon QuickSight?

Quick sight is a part of Amazon Web Service that helps in enabling to upgrade the business from a spreadsheet-based reporting to an interactive tool that can analyze the data more appropriately. It provides cost-effective, fast and extremely interactive business intelligence for an organization. So of the other reasons due to which an organization can choose Amazon Quick sight is as follows –

Provides High Data Sources Compatibility – QuickSight can read the data from any of the sources whether it is a CSV file or a SaaS data sources or any other file format. It can even read the data from any of the relational data sources like Amazon Athena, Amazon Redshift, Amazon Presto, S3, etc. Any other data sources can also be accessed by either linking or importing them.

Highly Scaling Capability – Amazon QuickSight is being used across several business domains for measuring the business metrics independently. Quick sight can easily be scaled up or down according to the need of the user. It can easily be scaled up across ten to thousands of users who can work independently and simultaneously across all the data sources.

Provides Smart Interactive Visualizations – The SPICE (Super-fast, Parallel, In-memory, Calculation Engine), helps to model fundamental processes and retrieves the data faster than usual. It has an in-built visualization tool that helps in generating a string of suggestions, and it does this by observing the patterns which exist in the back end data sets.

Provides High Portability – Here highly portable meant to be that, it can be accessed at any time and from any place. Amazon QuickSight is one of the handiest tools, as we can access it from our laptops, smartphones and even offline after installing it on offline mode. The only thing to do is, and we should quickly get through it.


Amazon Redshift with QuickSight

Redshift is one of the fastest growing services when coming to Amazon Web Services platform. Quick sight smoothly connects to the Redshift and gives the native access to all our instances and tables.

Authorizing Connections From Amazon QuickSight to Redshift Clusters

For connecting Amazon QuickSight to an Amazon Redshift instance, we must create a new security group instance. For manually authorizing QuickSight connections, we must know about how to manually enable the access to a Redshift cluster in a VPC or Virtual Private Cloud, and to do this follow the below-mentioned steps

  • Sign in to the AWS console and open the Amazon Redshift console with the help of below link – https://console.aws.amazon.com/redshift/
  • Next, select the details page icon, which is available next to the cluster which you want to make available.
  • Select the port under the Cluster Database Properties section, and note down the value of the port.
  • Select the VPC ID under the Cluster Properties section, and note the value of VPC ID.
  • Select the View VPCs for opening the Amazon VPC Management Console.
  • On the Amazon VPC Management Console, select the Security Groups under the navigation panel.
  • Select the Create Security Group.
  • On the Create Security Group page, enter the security group information which is being asked.
  • Click on Yes Create button.
  • Now the new security group will be displayed on the screen. Select the security group and the inbound rules and create a new inbound rule.
  • Click on Save button for saving the new inbound rule.
  • After that return to the Clusters page of the Amazon Redshift Management Console, and then open the details page for the cluster that you want to enable to access.
  • Select the cluster and then click on the modify button.

A Holistic Strategy

AWS Services for building a Unified Cloud Computing Platform for fast, cost effective analysis of data, generating insights in Real Time.To know more about AWS Services we advice taking the subsequent steps –


Related Posts


Leave a Comment

Name required.
Enter a Valid Email Address.
Comment required.(Min 30 Char)