Transforming NoSQL Data into Real-Time Insights: A Serverless AWS Analytics Pipeline.

The Challenge: How do we query data from DynamoDB, process it with SQL-like queries, and visualize it in QuickSight—all while keeping the solution scalable and cost-efficient? Solution: This serverless solution leverages Lambda for DynamoDB extraction, S3 for spill storage, Athena+Glue for SQL processing, and QuickSight for scalable visualizations—all without managing infrastructure. Architecture: Create a quicksight account: Setting Up DynamoDB: • Created a DynamoDB table with partition and sort keys. • Insert sample data in JSON format. Configuring Lambda as a Data Connector: • Set up an AWS Lambda function to query DynamoDB and return data in Athena-compatible format. • Set up IAM roles to allow Lambda to read from DynamoDB and write to S3. Querying Data in Athena: • Executed Athena SQL queries to filter and process data. IAM Role Configuration for QuickSight: • Granted QuickSight permissions to invoke Lambda and read from S3. • Updated IAM role policies for secure access. Glue’s background setup: Lambda extracts DynamoDB data to S3, with Glue automatically managing schema metadata for Athena querying. Building Interactive QuickSight Dashboards: • Created donut charts, bar charts, and tables to visualize task completion status. • Enabled live data updates from DynamoDB → Athena → QuickSight. Summary: From DynamoDB to dashboards in minutes Lambda transforms streams S3 stores efficiently Athena queries via Glue QuickSight visualizes All serverless. All cost-optimized

Apr 4, 2025 - 17:55

Transforming NoSQL Data into Real-Time Insights: A Serverless AWS Analytics Pipeline.

The Challenge:
How do we query data from DynamoDB, process it with SQL-like queries, and visualize it in QuickSight—all while keeping the solution scalable and cost-efficient?

Solution:
This serverless solution leverages Lambda for DynamoDB extraction, S3 for spill storage, Athena+Glue for SQL processing, and QuickSight for scalable visualizations—all without managing infrastructure.

Architecture:

Create a quicksight account:

Setting Up DynamoDB:
• Created a DynamoDB table with partition and sort keys.
• Insert sample data in JSON format.

Configuring Lambda as a Data Connector:
• Set up an AWS Lambda function to query DynamoDB and return data in Athena-compatible format.
• Set up IAM roles to allow Lambda to read from DynamoDB and write to S3.

Querying Data in Athena:
• Executed Athena SQL queries to filter and process data.

IAM Role Configuration for QuickSight:
• Granted QuickSight permissions to invoke Lambda and read from S3.
• Updated IAM role policies for secure access.