The “AI replacing humans” narrative is mostly noise. In reality, smart organizations are evolving: pairing humans with AI in decision loops that outperform either alone. This isn’t a revolution, it’s an evolution. And it’s already happening. This post explores what AI-augmented decision making really looks like in practice, not just on slides.

Data teams face constant challenges — from handling big data to ensuring quality and access. AI now works alongside us, writing code and generating tests. Beyond headline-grabbing tools like Copilot, lesser-known AI tools are quietly transforming data engineering. Here’s a curated list of underrated tools that can boost productivity in building pipelines, managing messy data, and maintaining data quality.

Modern data teams need flexible, scalable, and real-time methods of ingesting and transforming data. In this blog post, we’ll explore why the conventional approach of ETL is becoming obsolete and look ahead to the new ways of data ingestion that will define the future in 2025.

AI has grown leaps and bounds, transforming from basic, rule-based systems into something resembling futuristic companions. But let’s pump the brakes for a moment. What makes one AI agent “smart” and another “genius”? Inspired by the “levels of autonomous driving” framework, researchers have broken AI agents into levels of capability. Let’s explore these levels, what makes them tick, and why they matter.

AI has grown leaps and bounds, transforming from basic, rule-based systems into something resembling futuristic companions. But let’s pump the brakes for a moment. What makes one AI agent “smart” and another “genius”? Inspired by the “levels of autonomous driving” framework, researchers have broken AI agents into levels of capability. Let’s explore these levels, what makes them tick, and why they matter.

In today’s fast-paced, competitive world, the ability to make informed decisions is a superpower. Businesses that rely on intuition or gut feelings often find themselves left behind. Enter data-driven decision making — a methodical approach that leverages data to guide choices, solve problems, and drive success. This article dives into the what, why, and how of data-driven decision making, offering practical steps to help you start harnessing the power of data today.

In this article, we’ll explore the what, why, and how of data engineering and pipeline automation. We’ll also share real-world examples and practical steps to help you implement these processes in your own organization.