
Automated Data Analytics on AWS enables users to quickly derive operational insights from application logs across multiple data sources by ingesting, transforming, and querying diverse datasets through an intuitive interface without requiring specialized technical skills.


<div><p>This article demonstrates how to use AWS Automated Data Analytics (ADA) to derive operational insights from application logs across multiple data sources.</p><ul><li>ADA enables data analysts to ingest, transform, and query diverse datasets without specialist technical skills</li><li>Pre-built connectors support CloudWatch, S3, DynamoDB, Kinesis, and other AWS services</li><li>Demo uses Lambda-generated logs, historical S3 logs, and DynamoDB lookup tables as data sources</li><li>Custom Python transformations convert Apache Log Format into queryable fields</li><li>SQL queries join multiple data products to identify top error endpoints and patterns</li><li>ADA integrates with Tableau for visualization and dashboard creation</li><li>Heat maps and bar charts display HTTP error frequency by application endpoints</li></ul><p>ADA simplifies operational data analytics by automating ingestion, transformation, and querying of logs, enabling teams to gain insights in minutes without coding expertise.</p></div>


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