Blog
Introducing BuzzOps: A Tool to Translate Vendor BS. You’re Welcome.
These days, every vendor claims to be agentic, AI-native, and context-aware. We made a tool that explains what they really do.
TestGen Now Supports Oracle and SAP HANA, with a New Setup Wizard to Get You Running Fast
Two of the most common databases in large enterprises are now supported by open source and enterprise TestGen.
DataKitchen Enhances Its Support for Data Stewards to Manage Data Quality Tests in TestGen
Data stewards bear a difficult responsibility. They are the people in the organization who are supposed to define, document, and enforce data quality standards, yet in most organizations, they lack the tools to do so. They can't easily scope who sees what. They can't...
$1 Billion in Data Observability VC Investment: This Is Not Going to End Well
Too Much Money, Too Many Vendors, Your Problem You have probably noticed that your inbox is full of data observability or data quality vendor pitches, your conference has a dozen booths for tools that all look roughly the same, and somehow every budget conversation...
“We Just Eyeball Row Counts and Pray”
What Internet Communities Really Think About Why Data Engineers Don't Test TL;DR: We read 849 comments across 18 community threads on Reddit, Hacker News, Stack Overflow, and the dbt Community Forum. The #1 reason data engineers don't test: nobody gives them the time....
DataOps + FITT + Data Testing = 10x Data Engineering Productivity with AI
10x Your Data Engineering with AI: Practitioner Patterns That Actually Work Claude Code ( DataOps + FITT + Data Testing ) = 10x Data Engineering Productivity AI coding tools like Claude Code are generating significant excitement in software engineering. But for data...
The Equation For AI Success: DT + DX + CTX = 10x
Everyone wants AI to answer business questions with their data. The reality is most AI assistants built on enterprise data give mediocre, unreliable, or outright wrong answers — not because the AI is bad, but because the foundation underneath it is. Your AI chatbot is...
The DataOps Way to Data Quality: A Free Book for Every Data Team
We announce our third book, The DataOps Way To Data Quality & Data Observability. Data quality is not a technology problem. It never has been. The data industry has spent years chasing the next tool, platform, or vendor promise, yet data errors still dominate the...
Why Your Data Quality Dashboard Isn’t Working And What to Do About It
Why Your Data Quality Dashboard Isn't Working And What to Do About It Your organization has a data quality dashboard. You’ve put time and effort into visualizing metrics, tracking scores, and creating reports. But week after week, data quality barely improves. This...
We Got Roasted On Reddit For Asking ‘Why Data Engineers Don’t Test?’
How This Research Started (And Why We're Telling You) DataKitchen co-founder Gil Benghiat recently posted a question to r/dataengineering — one of the largest and most active data engineering communities on the internet. The question was genuine: "What is actually...
Be The First To Know: Smart, Continuous Table Monitoring Has Arrived In TestGen
If you're a data engineer tired of being the last to hear when something goes wrong, this is for you. You know the feeling: a business stakeholder messages you at 2 PM on a Tuesday saying, "Hey, the revenue numbers look off." You open your laptop and spend the next...
Data Quality Testing Is At The Core of Four Critical Data Team Processes
Every data and analytics team juggles multiple responsibilities. You are expected to ensure your data is accurate and fit for purpose. You need to prevent problematic data from entering your data environment. You must stop your data pipelines from delivering...
Stop Paying The Data Quality Tax
Why Data Quality And Data Observability Tools Cost So Much (And Why That's Ridiculous). You're paying enterprise prices for commodity algorithms. Here's what's really going on. We understand the struggle. Data pipelines fail, dashboards go stale, and someone in...
Data Quality vs. Data Observability: The Pets and Cattle of Your Data Estate
Data Quality vs. Data Observability: The Pets and Cattle of Your Data Estate If you've spent any time in DevOps circles, you've heard the phrase "cattle, not pets." Randy Bias popularized this analogy around 2012 to explain a fundamental shift in how we think about...
