Long-form essays from the engineers shipping AI inside payers, hospitals, energy operators and proptech platforms. Written for technology leaders who care more about what runs in production than what trended last week.
Is a data lakehouse right for your business? Find out when you should be using a modern data architecture that includes a lakehouse.
Discover how to create a rationale for your data infrastructure investment - ROI frameworks, cost modelling, and real-world examples.
Learn how to build, measure and report on metrics for data infrastructure strategy that actually drive performance and trust.
A clear step-by-step guide to help engineering teams successfully run a data infrastructure solutions PoC.
Understand how data infrastructure and analytics will evolve through 2027 with a focus on building AI-ready systems and consolidating platforms.
Learn how to audit your data infrastructure strategy, measure maturity, and build a scalable roadmap for reliability, observability, and AI readiness.
Discover the key data infrastructure trends that will influence 2027 and how engineering leaders can build AI-ready and scalable systems today.
Find out about data infrastructure careers in 2026, what's expected of engineers and developers within contemporary data platforms, and how to develop them for success in the future.
Discover the Data Infrastructure Solutions Vendor landscape for 2026-comparing vendors and categories while learning how best to choose the right platform.
Need to compare a data mesh vs a data fabric? Learn the key differences, how to weigh the trade-offs and determine which approach is right for your team in 2026.
Learn Data Warehouse Concepts in 2026 and how to use Architecture, Tools, and Best Practices to Build Scalable Analytics Systems.
A user's manual for sustainable, quality data through verification of modern data frameworks, as well as validation methods to eliminate production failures (or data loss).
Explore how DataOps and CI/CD for data pipelines enhance the reliability, speed, and scalability of DataOps as seen from an engineering leader's standpoint.
Are you selecting a data lakehouse? Find a review of Delta Lake, Apache Icebox, and Hudi that compares trade-offs of each, performance data points and examples.
Understanding how Apache Iceberg will change data lakehouse architecture (in 2026) for the better! An engineer’s guide to real-world experience
How the best engineering teams create frameworks for measuring, monitoring, and improving quality of large amounts of data.
Learn how to automate data infrastructure effectively, what to automate, what to avoid, and how to scale systems without adding complexity.
Get the low-down on how and when to use event driven architectures and data streaming (and why you should use them) with this practical guide to stream-based data architecture in 2026.
Use these eight strategies to make your data infrastructure perform better. A step-by-step reference for Data Engineering Leads and CTOs overseeing today's cloud infrastructures.
Learn how to design data infrastructure effectively with this simple guide to creating scalable and stable systems that are ready for AI.
Discover how to manage your data infrastructure expenses by eliminating waste, increasing efficiency, and scaling without overpaying.
Your Data Exists. But no one knows where it lives. No one trusts the data. No one understands how the data is being used. This is one of the biggest and most underestimated challenges in today's…
How e-commerce companies build scalable data infrastructure to process millions of daily events and provide real-time analytics, as well as support for AI.
Find out what causes your data pipelines to fail without warning and how you can use data infrastructure management, observability, and monitoring to quickly identify, prevent, and resolve…
One long-form essay every other Wednesday. Written by the engineers shipping production AI for our clients, not by a content team. No promotional emails. Unsubscribe in one click.
