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The Problem: Skyrocketing AWS Analytics Costs When managing analytics for our loan management system, we initially turned to the standard AWS stack: Amazon Redshift for data warehousing and AWS Glue for ETL pipelines. The result? A shocking $800 bill...

Problem You can see "data scanned" metrics for queries in the Redshift console, but you need to access these numbers programmatically from Lambda functions, ETL jobs, or CI/CD pipelines that use the Redshift Data API. Without programmatic access to s...

Problem Developers frequently ask "How do I write optimized Redshift queries from the start?" after experiencing slow performance, unexpectedly high costs, and frustrated business users waiting for critical reports. Clarifying the Issue This isn't ab...

Problem Teams using Amazon Redshift often struggle with a paradox: they know Redshift excels at analytical workloads and can support focused data marts, but when it's time to build one, they face decision paralysis. Should they create a full enterpri...

Most traditional data catalogs and metadata systems perform only full extractions: querying metadata for every object in the source system — tables, views, columns, ownership, tags, descriptions — on every scheduled run. While this ensures completene...

Does serverless computing on AWS matter? In today’s cloud-first world, organizations are under increasing pressure to deliver more, faster, and often with fewer resources. Serverless computing on AWS has emerged as a game-changer, allowing companies ...
