@anomalyarmor
data observability
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Nothing here yet.
Feb 2 · 8 min read · Chat interfaces are table stakes. Proactive intelligence is next. Your data observability tool just sent you 47 alerts. Three dashboards are showing anomalies. A stakeholder is asking why the numbers in their report changed. You open your "AI-powered...
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Jan 26 · 4 min read · When you connect a data quality tool to your database, you're trusting that tool with access to your data. Most tools ask you to just trust them. We decided to show our work. Every query AnomalyArmor runs against your database goes through our Query ...
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Jan 19 · 5 min read · Every data quality vendor has a features page with the same checkboxes. Schema monitoring. Freshness tracking. Anomaly detection. Column profiling. The features are table stakes. What separates the good tools from the mediocre ones is everything else...
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Jan 13 · 4 min read · Unlike a crashed server or a failed deployment, schema drift doesn't announce itself. There's no error page. No alert. Your pipelines keep running. Your dashboards keep updating. The numbers just quietly become wrong. How it happens Schema drift happ...
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Jan 5 · 4 min read · I've done data engineering over the years at CJ, Savings.com, MySpace, Chegg, LinkedIn, Microsoft, One Medical, and AbnormalAI. The thing that's always stuck with me is how the job gets harder in a way that sneaks up on you. When you build a pipeline...
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