Case Study

Amazon QuickSight Dashboard Implementation for an E-Commerce Industry

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Industry 

E-commerce

Expertise 

Amazon EC2, Amazon S3, Amazon Athena, Amazon QuickSight, AWS Lambda

Offerings/solutions 

Automated Report Generation with Python AWS Glue Crawlers Athena QuickSight

About the Client

The client is a Bangalore-based company that empowers businesses to accelerate their revenues online. They have empowered brands to scale up for almost a decade across multiple verticals. They are dedicated e-commerce digital partners who are happy to plan, strategize, and implement a complete digital roadmap for your e-commerce offering.

Highlights

100%

Automation Efficiency

Daily updates

Real-Time Reporting

Customized Access Control

User-Based Permissions

The Challenge

The client needs an interactive Amazon QuickSight dashboard to visualize daily sales performance, categorized by individual orders. The report must include key performance indicators such as total sales, Revenue, Top Brands, FC Zone, UPO etc. sourced from platforms like Amazon, Flipkart, vinculum etc. Previously, the client manually generated these reports, and now seeks automation for the entire process.

Solutions

  • Automating the creation of reports eliminates the necessity for manual labor, thereby saving time.
  • Python scripts are employed on Amazon EC2 to automate data retrieval directly from the source, ensuring the generation of precise reports.
  • There are 3 AWS Glue Crawlers running on this bucket which creates the raw tables in the database.
  • These crawlers are set to run daily to update the latest data and create the n partitions.
  • Amazon Athena is used to create the dataset based on the tables that are created in the glue catalog for the main data partition i.e. tables for the n partitions.
  • Amazon QuickSight is employed to extract actionable insights by accessing data from the Amazon Athena table.
  • Created interactive dashboards using the datasets based on the clients’ requirements.

The Results

Automated data gathering and processing using Python, multiple file joins and table views created with Amazon Athena, daily data updates, and user-specific access for dashboarding and reports.

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