Why do data teams happily let AI write their SQL, but won't let AI test it?
Per dbt's 2026 survey: 72% use AI for code, 24% for pipeline monitoring. A 48-point gap.
https://t.co/anNfX1ZciE
#dataengineering#dataobservability#dbt
Data observability looked very different a year ago.
Metaplane got bought by Datadog. Monte Carlo cut 30%. dbt eats Elementary. Acryl absorbs DataHub.
Here's how I'd actually pick a tool today:
https://t.co/8i8dwVOFNK
#dataengineering#dataobservability
Schema changes break dashboards silently.
How do you monitor schema changes in Snowflake, Databricks, and Postgres using INFORMATION_SCHEMA + a daily diff?
https://t.co/lJIIlShWlf
#dataengineering#dataquality#snowflake#databricks
Shipped in AnomalyArmor: every asset's monitoring config exports as Open Data Contract Standard (ODCS) YAML.
Click Export, get portable YAML. Diff it in Git. Import it into any ODCS tool. Your config travels with you.
#DataContracts#ODCS#DataEngineering#DataQuality
What does downtime look like when you have an ETL failure? For those new to the industry, here are some tips that may help you out.
Walk through the anatomy of a data downtime incident and how to actually measure it:
https://t.co/OCkfnAWHEB #DataEngineering#DataObservability
AnomalyArmor is now live on @glamaai π
https://t.co/nkvmh9Lg4j
53 MCP tools for data observability β alerts, freshness, schema drift, lineage β queryable by any AI agent that speaks MCP.
OAuth 2.1 at https://t.co/vS5RPimz7Z
#MCP@glama_ai
Most data tools are invisible to AI agents. Their docs are JS-gated, they're not in MCP registries, their robots.txt blocks GPTBot.
We fixed it. Result: #2 of 6,242 on https://t.co/2wS3oDiqrx for agent readiness.
npx skills add anomalyarmor/agents
@AnthropicAI#MCP@cursor_ai
This might be the most important score your website will ever get.
Agents are about to become the #1 source of traffic on the internet. Sites that aren't ready will disappear.
https://t.co/uRm7J0IbPJ spawns real agents on your site and tells you exactly where you stand.
Scan your site in 1 minute β https://t.co/uRm7J0IbPJ
Cloudflare shipped https://t.co/AEjZRqO5Zg today. It scores how well you serves AI agents.
https://t.co/6XcvKnPJ3a: 100/100
What it means: AI agents can use AnomalyArmor today
β’ MCP server
β’ An in-app agent
β’ APIs, SDKs
#AIAgents#MCP#DataEngineering#buildinpublic
@Cloudflare https://t.co/6XcvKnPJ3a: 100%
We've been treating AI agents as first-class readers for a while: llms.txt, Claude MCP server, structured content on every page. Nice to see a standard tool for the rest of the web.
Do you know the 6 dimensions of data quality? Accuracy, completeness, consistency, timeliness, validity, uniqueness. Each one breaks differently. SQL examples for detecting all 6 in production. https://t.co/0iWbBxE3QU #DataQuality#DataEngineering#DataObservability#dbt#sql
The UI era is ending. πͺ¦
For 70 years we designed computer interfaces. Mainframe, CLI, GUI, Touch.
But with AI, the interface is disappearing. What will come next?
My talk from @mastra's conf this week:
New homepage is online. Click from a list of pre-selected prompts to see AI in action with live demo data. Comes with a 14-day trial. Use this while I'm still convinced this is a good idea. #dataobservabililty#anomalyarmor#schemadrift#ai https://t.co/QzVUFWKwFZ
Schema drift is the #1 cause of silent data failures.
A column gets renamed. Pipelines keep running. Dashboards show wrong numbers.
Here we set up data observability in 30 seconds. #dataengineering#dataobservability#dataquality#schemadrift
https://t.co/wvKa4FjUW3
@DataSynthGen Hire the people that do not hoard documentation. Beyond that, set up processes to prevent lost knowledge. A nice feature of AI (and something AnomalyArmor leans on) is to look at table objects and data to understand the objects purpose.
Engineers leaving and taking with them tribal knowledge is always a problem. We can't prevent that, but we can give you the tools to quickly and with little effort set up test coverage for data that you now own. #dataobservability#dataquality