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Anomalo

Automated data quality monitoring that learns your data patterns and alerts you to issues before they impact your business.

Enterprise
150+ users
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Overview

Anomalo is an automated data quality monitoring platform that uses machine learning to understand your data patterns and detect anomalies without requiring manual rule configuration. The platform focuses on zero-configuration setup, learning from your historical data to establish baselines and identify deviations.

Founded by former Google and LinkedIn engineers, Anomalo emphasizes ease of use and intelligent automation. Their approach reduces the burden on data teams by automatically discovering what's normal for your data and alerting only when genuine issues occur.

Key Features

Automated Monitoring

Zero-config setup that learns your data patterns automatically

Root Cause Analysis

Intelligent investigation of data quality issues

Custom Metrics

Define business-specific data quality metrics

Smart Alerting

Contextual notifications with Slack and email integration

Pros
  • True zero-configuration setup
  • Intelligent alerting reduces noise
  • Good integration ecosystem
  • Fast time to value
  • Strong customer support
Cons
  • Limited customization options
  • Relatively new to the market
  • Pricing not transparent
  • May miss edge cases that require manual rules
Best For

Busy Data Teams

Teams that want monitoring without manual configuration

Growing Companies

Organizations scaling their data operations

Cloud-First Teams

Modern data stacks with cloud data warehouses

Customer Success Story

Discover Financial

Financial Services

"Anomalo provides automated anomaly detection, helping us maintain data quality across our financial systems."

Source: anomalo.com