Case Study

A Digital Media Company Modernizes its Infrastructure and Enhances Data Insights with Amazon DynamoDB

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Digital Media


AWS Lambda, Amazon DynamoDB, Amazon API Gateway, Amazon Comprehend, Amazon Rekognition, Amazon CloudFront, Amazon S3


Centralized data orchestration boosts productivity by 80%, while AI/ML automation with Amazon DynamoDB saves 50% in costs and enhances operational efficiency

About the Client

The Morung Express is an independent English language newspaper which provides an alternative voice to the dominant status quo. They are based out of Nagaland, India, The Morung Express was conceived from the Naga people’s historical realities and is guided by their voices and experiences. It is the first print newspaper in Nagaland with an online edition.



Increase in Data Productivity


Cost Savings

Implementation of AI/ML and Amazon DynamoDB

Enhanced Operational Efficiency

The Challenge

The client encountered challenges with on-premises infrastructure due to inconsistent data, leading to frequent updates in the relational database and reducing accessibility and efficiency. The client intends to leverage the AWS ecosystem, such as Amazon DynamoDB, AWS Lambda, Amazon S3, and pre-trained AI services, like Amazon Rekognition, to analyze user data and provide insights for faster decision making.


  • The solution depicts storing, analysing and organizing metadata into Amazon DynamoDB which enables efficiently accesiblity based on Object Detection Entities and Celebrity Detection Entities.
  • Amaozn DynamoDB plays a crucial role for storing the AI-processed metadata and user defined metadata pertaining to the uploaded objects acting as a primary database.
  • Objects uploaded on Amazon S3 via the pre-signed URLs trigger Lambda on Amazon S3 PUT event which records an entry in Amazon DynamoDB table with user-defined metadata.
  • The Amazon DynamoDB stream is utilized to filter and process files based on the file type to perform various tasks, such as Amazon Rekognition  to detect Entities and Amazon Comprehend to detect key phrases.
  • Data is stored in Amazon DynamoDB using proper naming convention based on the user’s metadata, improving the accessibility through the web application.
  • Amazon DynamoDB stores the data like UID, Date/time, Description, Manual Tags, s3 URL, S3_Location, Upload_format, and user information having proper partition and sort keys making it easy for querying the data.
  • Implemented a CI/CD leveraging AWS services like AWS CodeBuild, AWS CodePipeline to automate code deployments stored on AWS CodeCommit.
  • The AWS services leveraged in building the solution are AWS Lambda, Amazon DynamoDB, Amazon API Gateway, Amazon Comprehend, Amazon Rekognition, Amazon CloudFront, and Amazon S3.

The Results

Centralized data orchestration increased productivity by 80%, and AI/ML automation with Amazon DynamoDB saved 50% in costs while enhancing operational efficiency by eliminating manual labor and improving data accessibility and resource utilization.

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