Anomalo
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About
Anomalo is an AI-powered automated data quality monitoring platform for enterprises. It helps businesses build trust in their data by rapidly detecting, analyzing, and resolving data quality issues before they impact operations. Anomalo uses unsupervised machine learning to understand data patterns, identify anomalies, and provide automated root cause analysis. It integrates with various data sources and offers custom data validation and KPI tracking, all without requiring code. The platform is designed for scalability and enterprise-level security, with SOC 2 compliance and secure in-VPC deployment. It supports data profiling and lineage, helping teams quickly address and resolve issues. Anomalo's customers include industry leaders like Discover Financial and Notion.
Platform
Task
Features
• data validation
• anomaly detection
• automated root cause analysis
• data governance
• data observability
• data lineage
FAQs
What data quality monitoring techniques does Anomalo utilize?
Anomalo uses a mix of techniques: metadata-based observability for all tables, AI-based anomaly detection for value monitoring, and user-defined rules for custom checks.
Does Anomalo provide data lineage tools?
Yes, data lineage information is shown for each monitored table, pulled directly from the data warehouse/lakehouse. This helps diagnose issues and understand impact.
Does Anomalo provide data profiling and analysis?
Yes! Data profiling (value distribution per column) and visualizations for each check are available. Key metric monitoring generates charts and notifications.
What kind of custom data quality monitoring does Anomalo offer?
Anomalo offers out-of-the-box automation, but allows user-defined validation rules or metric tracking via UI (no-code) or API. SQL checks and API integration are also possible.
Why is data quality monitoring important?
Data quality monitoring prevents bad data from harming business. It addresses broken products, inaccurate reporting, and erratic AI models. Trustworthy data drives better decision-making.
How does Anomalo ensure data quality at scale?
Anomalo offers data observability (low-cost metadata monitoring), automated AI-powered checks (sampling and inspecting data values), and custom rule creation. AI algorithms learn from data to adapt and alert.
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