An Intellyx Brain Candy Update
Anomalo combines machine learning and AI inference capabilities concentrated on finding, reporting and resolving problematic data quality issues at scale within massive data lakes and pipelines.
Since our 2024 briefing with this well-backed startup, they have put the pedal to the metal on partnerships with most of the leading cloud data warehouse and data catalog vendors on the market. Sure, those platforms usually have some kind of automated utility to check data for validity and format before and after a transformation, but they don’t really dig deeper than the cellular level or point out issues within the content itself, much less interact with other data sources and streams.
For believers in the 80/20 rule of thumb, Anomalo reports that their ML routines and AI observability can learn to find and resolve 80% of data anomalies without human intervention, while providing human data stakeholders with alerts, low-code declarative rule-building, and metrics to pinpoint and triage the remaining 20% of troublesome issues.
Unstructured data assets such as documents and conversation logs can also get the same quality treatment, which is critical for modernizing a data estate without stressing out the team on manual testing, or maxing out cloud compute and storage bills on quality and compliance.
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