Project Report: Superstore Data Analysis using AWS

Author: Jesna Menezes Date: April 30,2026

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Table of Contents

1. Project Overview
2. Architecture Diagram
3. Step 1: Identity and Access Management(IAM) User Creation
4. Step 2: Simple Storage Service(S3) Bucket
5. Step 3: AWS Glue and Data Catalog
6. Step 4: AWS Athena
7. Step 5: Amazon Quicksight

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1. Project Overview

This document outlines the step-by-step process to creating a end-to-end superstore data analysis using various AWS services.

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2. Architecture Diagram

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3. Step 1: Identity and Access Management(IAM) User Creation

• Navigate to IAM and click on Create User

• Specify the usedetails and enable Provide user access to the AWS Management Console - optional

• Attached admin access directly to the user under set permissions.

• The user is created as below,

  

• Login using IAM user credentials

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4. Step 2: Simple Storage Service(S3) Bucket

• Navigate to S3 and click on Create bucket

• Create a general purpose bucket with a unique bucket name in the specific AWS Region.

• Create a orders folder in the S3 bucket.

• Download the Superstore Dataset(https://www.kaggle.com/datasets/vivek468/superstore-dataset-final) from Kaggle.

• Select only data with order date 2017-01-01 and upload the same to folder orders/snapshot_day=2017-01-01/

  

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5. Step 3: AWS Glue and Data Catalog

• Navigate to AWS Glue-> Databases -> Add Database

• Create a Database as below,

• Navigate to AWS Glue->Crawlers->Add crawler

• Create a crawler on S3 bucket

• Add a IAM user Role for the AWS services to use

• Run the crawler on the data available to create a table definition without storing the data. This is creating the Data catalog/meteadata for the data.

• Partition is also created based on the folder name.

• Upload the data for next few dates and run the crawler on the same.

  

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6. Step 4: AWS Athena

• Navigate Athena->Query Editor

• Select the appropriate Databa source and Database

• Create a S3 folder to save the Athena results

• Preview the orders table

  

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7. Step 5: Amazon Quicksight

• Navigate to Quicksight
• Create the Database under Athena
• Start analysing the data using quicksight and create the dashboard and publish the same.

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