data engineering

For those who work in data science, data engineering, or as as a frontend/backend developer, you cope with JSON. For professionals, its principally only death, taxes, and JSON-parsing that's inevitable. The problem is that...

, having spent my profession working across a big selection of industries, from small startups to global corporations, from AI-first tech corporations to heavily regulated banks. Over time, I’ve seen many AI and ML...

the ultimate quarter of 2025, it’s time to step back and examine the trends that may shape data and AI in 2026.  While the headlines might concentrate on the most recent model releases and...

— We’ve Been Down This Road Many who've come before have bemoaned the analytics dashboard. Dashboards may contain a variety of information but not much in the way in which of insight. They could...

0. Introduction (SFC) are fascinating mathematical constructs with many practical applications in data science and data engineering. While they might sound abstract, they’re often hiding in plain sight—behind terms like Z-ordering or Liquid Clustering...

(or 2010s to be more precise) big-data boom brought the emergence of specialization in data roles. What was solely described as “Business Intelligence Engineer” was further broken down into Business Intelligence Engineers/Analysts, Data...

The aim of this text to offer the reply to the query: “Which one is ‘higher’ — Import or Direct Lake?” since it’s unattainable to reply, as there is no such thing...

tools like dbt make constructing SQL data pipelines easy and systematic. But even with the added structure and clearly defined data models, pipelines can still develop into complex, which makes debugging issues and...