BEBlaine Elliottinblog.anomalyarmor.ai·May 11 · 14 min readWhy Do Data Teams Use AI to Write Code but Not to Monitor Pipelines?The AI gap in analytics engineering is a 48-percentage-point difference between how many data teams use AI to write code (72%) and how many use AI to monitor, test, or observe their pipelines (24%). It is the single most important structural finding ...00
BEBlaine Elliottinblog.anomalyarmor.ai·May 4 · 15 min readWhat Tools Should I Use for Data Observability in 2026?The best data observability tool depends on your warehouse, team size, and budget. If you want a short answer: full-platform tools like AnomalyArmor, Monte Carlo, and Metaplane offer the fastest time to value. Open-source tools like Great Expectation...00
BEBlaine Elliottinblog.anomalyarmor.ai·Apr 27 · 13 min readHow Do I Monitor Schema Changes in a Data Warehouse?You monitor schema changes in a data warehouse by periodically querying metadata catalogs (like INFORMATION_SCHEMA), subscribing to event-driven notifications, or comparing structural hashes of your tables over time. Each method trades off between de...10
BEBlaine Elliottinblog.anomalyarmor.ai·Apr 20 · 19 min readWhat Is Data Downtime and How Do You Measure It?Data downtime is the total period during which data is missing, erroneous, or otherwise unfit for use. It is the data equivalent of application downtime: the window between when something breaks and when it is fully resolved. During data downtime, da...00
BEBlaine Elliottinblog.anomalyarmor.ai·Apr 12 · 3 min readState of Data Engineering 2026: Why Data Teams Spend 60% of Their Time FirefightingIt's 9am. You planned to build a new pipeline today. Instead you're debugging why the revenue dashboard shows zeros, tracing a stale table through three upstream dependencies, and explaining to a VP that yesterday's numbers were wrong. By noon you've...00
