Data Quality
What Is a Data Contract and Do You Actually Need One?
A data contract is enforced in the producer's pipeline. Most teams asking for one actually want monitoring. How to tell which you need.
Data Observability
Data Quality
dbt Tests vs Data Observability: Where Each One Stops
dbt tests check assertions you wrote, at build time, on tables dbt owns. Every word in that sentence is a boundary. Here is what lives outside each one.
Data Quality
What Is the Best Datafold Alternative in 2026?
Datafold's CEO wrote in March that data quality "didn't pan out" as a category, and pivoted. If you bought it for data quality, that is your answer.
Data Quality
What Is the Best Elementary Alternative in 2026?
Elementary is genuinely open source and genuinely good. The question is what happens to the tables dbt never touches, and what June's merger changed.
Data Quality
What Is the Best Soda Alternative in 2026?
Soda's 2026 pricing is public, Soda Core is no longer open source, and nobody exports to ODCS. An honest comparison, including where Soda wins.
Data Observability
Data Quality Agents Compared: Monte Carlo, Acceldata, and the Agent-Native Approach
Monte Carlo, Acceldata, and Datadog's Metaplane all ship data quality agents now. Most are a language model bolted onto a legacy dashboard. Here's an honest comparison of the agent approaches and where an agent-native tool fits.
Data Quality
What Is a Data Quality Agent?
A data quality agent is software that watches your warehouse, investigates problems, and explains them on its own, instead of making you check a dashboard. Here's what that means, how it differs from rule-based monitoring, and why the category showed up in 2026.
Data Observability
OKF vs RAG for Data Warehouse Context: Why We Chose a Living Knowledge Base
Google's Open Knowledge Format (OKF) formalizes the "LLM Wiki" pattern: give an agent a curated markdown knowledge base instead of RAG over raw chunks. We've run a variation of that for warehouse context since 2025. Here's why a living knowledge base beats RAG, and where RAG still wins.
Data Observability
Citations for Your Data Incidents: Introducing EvidenceCapsule
When an AI agent answers "why is this table stale?" the hardest question is whether you can trust the answer. EvidenceCapsule is a typed investigation output where every claim cites the row it came from, so you can click through and verify.
Data Observability
How AI-Native Data Observability Changes Incident Response
Most data observability tools shorten the time to know something broke. AI-native observability shortens the time to know what broke, what depends on it, and what to do next. Here is what that workflow actually looks like during a real incident.
Data Quality
How Much Does Data Observability Cost in 2026?
Data observability costs range from $0 open-source (you pay in engineering time) to five-figure enterprise contracts. This guide breaks down every pricing model, the hidden costs nobody quotes, and a total-cost formula you can run on your own warehouse before any sales call.
Data Quality
How to Catch Silent dbt Test Failures Before They Hit Dashboards
dbt tests fail silently more often than they fail loudly. Warn-severity tests, skipped models, freshness gaps, and tests that only run in CI all let bad data through without paging anyone. This guide covers the patterns that hide failures and how to catch them.