Data Quality
What Is the Best Anomalo Alternative in 2026?
Anomalo's unsupervised ML is the real thing. Ask what it costs, what it explains, and whether you have the history to feed it.
Schema Drift
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 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 Engineering
How to Get Lineage From a dbt Manifest Without a Migration
Your dbt project already contains a complete dependency graph. It is sitting in target/manifest.json, and getting it out takes one command.
Data Quality
How Do You Know Your Data Quality Agent Is Right?
An agent's confidence score tells you what kind of evidence it found, not whether it is right. Four checks that separate a citation from a guess.
Data Engineering
How Do You Find the Blast Radius of a Broken Table?
One table breaks and forty alerts follow. Lineage turns that noise into a named root cause and a list of exactly what went stale.
Data Quality
What Is the Best Great Expectations Alternative in 2026?
Great Expectations is free to install and expensive to maintain. What the alternatives change, and how to port your suites without losing them.
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.
Data Quality
What Is the Best Bigeye Alternative in 2026?
Bigeye is an enterprise data observability platform priced for enterprise procurement. An honest comparison with AnomalyArmor: what Bigeye does well, where its pricing and sales model is a mismatch for mid-market teams, and when each tool is the right call.