Blog
Technical deep dives, AWS data engineering, and practical AI — written for engineers and technical decision-makers.
Shopify says $180K. Meta claims it drove $240K. Google Ads takes credit for $95K. Add them up and you 'made' more than you actually did. Here's why every platform lies to you — and how to get one number you can trust.
Platform ROAS tells you what each channel claims. Blended ROAS tells you the truth: total revenue divided by total ad spend. Here's how to calculate it properly, why it's the only number your P&L cares about, and the traps that quietly inflate it.
Shopify says $180K. Meta claims it drove $240K. Google Ads takes credit for $95K. Add them up and you 'made' more than you actually did. Here's why every platform lies to you — and how to get one number you can trust.
Platform ROAS tells you what each channel claims. Blended ROAS tells you the truth: total revenue divided by total ad spend. Here's how to calculate it properly, why it's the only number your P&L cares about, and the traps that quietly inflate it.
Your revenue history, customer LTV, and channel performance all live inside tools you rent. The day you stop paying — or a platform changes its API — it's gone. Here's why owning your data warehouse matters, and what it actually takes.
Exploring how GenAI is revolutionizing data engineering workflows, from automated pipeline generation to intelligent data quality monitoring.
A comprehensive guide to designing and implementing enterprise-grade data lakes using AWS services, based on real-world experience.
A deep dive into architecting real-time analytics solutions using AWS services like Kinesis, Lambda, and QuickSight for immediate business insights.
Learn how to design and implement scalable data pipelines using AWS services like S3, Lambda, and Glue for efficient data processing and analytics.
Practical AWS data engineering and AI — occasional, no spam, unsubscribe anytime.