Visualizing Big Data with AWS S3 and QuickSight: A Step-by-Step Guide

In this blog, we will learn how to use AWS S3 and QuickSight to create a visualizing dashboard from a large dataset.

Download Dataset: https://github.com/dhanush-bm/AWS-Quicksight

• The data is about Amazon bestseller products and is taken from Bright Data, a leading data collection company that collects public web data.

Step 1: Create a new bucket in S3 with the required name and the rest of the settings as default.

Step 2: Open the manifest.json file downloaded from GitHub and change the bucket name to the created bucket name.

Step 3: Open the newly created S3 and Upload both the csv and manifest files.

Step 4: Search for QuickSight in the search bar and sign up for QuickSight.

Step 5: Start a free trial of Enterprise Edition and make sure to cancel a subscription before 30 days to avoid unnecessary charges.

Step 6: Enter your name and email to create a QuickSight account.

Step 7: Make sure you select the S3 bucket that you want to link to QuickSight.

Step 8: Click on your S3 bucket and then finish. Keep the rest of the settings as default, and click Finish.

Step 9: Give it a couple of minutes for your QuickSight account to be created, and you will see QuickSight interference.

Step 10: Open a new tab and Open the manifest.json file uploaded to your Amazon S3 bucket. Click Copy S3 URI.

Step 11: Going back to QuickSight, Go to Datasets>New dataset >S3.

• Paste the URI copied from the S3 bucket, enter the required name for the data source, and connect.

Step 12: After dataset creation, click visualize.

Step 13: Enter the required layout, optimize the size for viewing and Create.

Step 14: Use QuickSight to create a dashboard with different visual types.

One solid advantage of Amazon QuickSight when compared to other visualization tools is its native integration with AWS data sources and services. As part of the Amazon Web Services (AWS) ecosystem, QuickSight seamlessly connects and interacts with various AWS data storage and processing services, providing a unique advantage for organizations already utilizing AWS services.

Here are some key points that illustrate this advantage:

Easy data integration: QuickSight allows you to directly connect to a wide range of AWS data sources, such as Amazon S3 for data storage, Amazon Redshift for data warehousing, Amazon RDS for relational databases, and more. This native integration simplifies the process of accessing data and reduces the need for complex data transformations or ETL (Extract, Transform, Load) procedures.

Faster data access: As QuickSight is designed to work closely with AWS data services, it can take advantage of the underlying AWS infrastructure’s speed and performance. This means that data retrieval and processing can be highly optimized, resulting in faster data access and real-time or near-real-time insights.

Secure data handling: AWS offers robust security measures, and QuickSight inherits these security features. Data accessed through QuickSight remains secure, encrypted, and compliant with industry standards, giving users peace of mind regarding data protection.

Scalability: QuickSight benefits from the scalability of the AWS cloud. It can handle large volumes of data and user interactions without compromising on performance. As your data and user base grow, QuickSight can easily scale to meet the increasing demand.

Cost-effectiveness: If your organization is already using AWS services, the native integration with QuickSight can lead to cost savings as you don’t need to invest in additional data connectors or pay for third-party integrations.