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The 2026 Data Quality and Data Observability Commercial Software Landscape
With 50+ vendors to choose from, data quality and data observability software has never been more powerful, more plentiful, or more confusing—until now.
Sure, Go Ahead And Feed That Data To The LLM … What Could Possibly Go Wrong?
Welcome to Analysis-A-Palooza: The Festival No Data Engineer Asked For
Webinar: Data Quality, DataOps, and Large Language Models
Data Quality, DataOps, and Large Language Models Struggling to bring order to the data and AI chaos?The reality for many data teams is often an unproductive mix of broken pipelines, reactive problem-solving, and “good enough” data that leads to poor...
You’re Thinking About Data Products All Wrong
Data Products Are a 'How,' Not a 'What.' When data team leaders hear "data products," they immediately think of the stuff they produce: dashboards, datasets, models, and warehouses—but focusing on the "what" completely misses the massive shift that data products...
The 2026 Open-Source Data Quality and Data Observability Landscape
When AI Meets Bad Data, Everyone Loses: A Definitive Guide for Data Engineers, Data Quality Professionals, and Data Team Leaders; October 2025 Your LLM just told the CEO that revenue is up 40% when it's actually down. Your analytic engineers are vibe coding late into...
Webinar: The FITT Way To Data Products: A New Data Architecture For A Product-Centric World
Transform Your Data Engineer Team from Firefighters to Data Product BuildersShift your data-architecture-focused thinking to a data-engineering-productivity-focused design. FITT democratizes system ownership, enables junior developers to contribute confidently, and...
DataOps Data Quality TestGen Expands: Now Supporting BigQuery and Apache Iceberg
We're excited to announce two major expansions to DataOps Data Quality TestGen Enterprise that bring intelligent data quality testing to even more of your data ecosystem. Whether you're working with Google BigQuery or managing file-based data through external tables,...
Process Guardianship: The Most Valuable Data Engineering Work You’re Probably Not Doing
The Hidden Crisis in Data Teams: When Business Logic Lives Everywhere and Nowhere There's a quiet crisis happening in data organizations everywhere. Not the dramatic kind that makes headlines—no security breaches, no system failures. Instead, it's a slow erosion of...
Flip the Script on Data Quality: Shift Left, Shift Down, and Take Control
How do you engineer quality into Data and Analytics Systems? There has been considerable discussion lately about data contracts and the shift-left approach in data and analytics systems. The manufacturing industry learned decades ago that catching defects early in...
FITT vs. Fragile: SQL & Orchestration Techniques For FITT Data Architectures
SQL & Orchestration Techniques For Functional, Idempotent, Tested, Two-Stage Data Architectures If you're tired of your data transformations randomly breaking, producing different results for no apparent reason, or taking forever to debug when something goes...
Data Quality Test Coverage In a Medallion Data Architecture
Data quality test coverage has become one of the most critical challenges facing modern data engineering teams, particularly as organizations adopt the increasingly popular Medallion data architecture. While this multi-layered approach to data processing offers...
Critical Data Elements: Your Shortcut to Data Governance That Actually Works
The Harsh Reality of Data Governance 💥 80% of data governance initiatives fail. Not because of tools. Not because of frameworks. But because the business isn't involved, and no one agrees on what data truly matters. That's where Critical Data Elements (CDEs) change...
We’ve Been Using FITT Data Architecture For Many Years, And Honestly, We Can Never Go Back
TL;DR: Functional, Idempotent, Tested, Two-stage (FITT) data architecture has saved our sanity—no more 3 AM pipeline debugging sessions. Picture this: It's 2:47 AM, your Slack is buzzing with alerts, and the CFO's quarterly report is broken because somewhere in your...
Webinar: Test Coverage: The Software Development Idea That Supercharges Data Quality & Data Engineering
In software engineering, test coverage is non-negotiable. So why do most data teams still ship data without knowing what’s tested—and what isn’t? Explore how leading data teams are applying the proven discipline of test coverage to data and analytics—automating...
