AWS Enterprise Data Lake

A media conglomerate had petabytes of unstructured clickstream and log data residing in disparate silos. Data scientists were spending 70% of their time on data preparation rather than analysis, and the costs of storing this data in traditional databases were spiraling out of control.

They needed a centralized, cost-effective way to store, discover, and query this 'dark data' without the overhead of a formal warehouse for every specific use case. Data accessibility was limited to a few 'gatekeepers', creating a massive bottleneck for innovation.

I architected and deployed a multi-tier Data Lake on AWS using S3 as the storage foundation. I utilized AWS Glue for automated metadata crawling and ETL, and implemented Amazon Athena to enable analysts to run ad-hoc SQL queries directly on the S3 data.

The architecture follows the Bronze/Silver/Gold pattern, graduating data from raw logs to cleaned, partitioned Parquet files. I also implemented fine-grained access control using AWS Lake Formation to ensure security and compliance.

I also integrated a 'Data Catalog' using AWS Glue that allows non-technical stakeholders to search for and understand the available datasets, democratizing data access across the entire media group.