Data Monitoring

Real-time data quality monitoring

Gain granular observability into the health of your data and identify data quality issues in real time.

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Uncover hidden insights

Easily identify data quality issues and take appropriate action. Anodot automatically analyzes the vast volumes of data to detect anomalies in topline data health KPIs:

Freshness

Distribution

Volume

Schema

Lineage

Pipelines

Can you effectively manage your data health?

As companies rely on more and more data to power increasingly complex pipelines, it’s imperative to keep this data reliable and accurate. Data pipelines can break for a million different reasons — from schema changes, through null values to duplication. But when data breaks you need to know, and fast: even a stale table or erroneous metric left unchecked can have adverse downstream repercussions in the form of data downtime, time-consuming data fire drills, loss of revenue, and erosion of trust.

Since data throughout the organization is so volatile and complex, static monitoring approaches based on dashboards and manual thresholds aren’t sensitive, robust or agile enough to effectively monitor the health of the data in your systems. With today’s data volume, velocity and variance, AI/ML-based monitoring with complete data coverage and early detection of data quality and discoverability issues is essential for eliminating periods of data downtime. With Anodot data quality issues are identified and addressed in real time so that data professionals can ensure continuous data reliability and accuracy.

Integrate your data sources

Anodot uses patented technology to autonomously monitor 100% of your data in real-time. Simply use our API or one of our built-in collectors to integrate data from applications, databases and streams for a comprehensive, correlated understanding of data quality anomalies. Anodot learns the normal behavior of all your data health metrics and constantly monitors their every move.

Actionable insights in real-time

Anodot autonomously distills billions of events into the single spot-on alerts that you need to know about right now, so you can detect data quality issues faster. Anodot’s patented correlation engine groups correlated anomalies and identifies all events and contributing factors for each incident, for the fastest time to resolution. Alerts are seamlessly integrated into your existing workflow through text, email, Slack, Jira, Webhook, PagerDuty or any of your other favorite channels.

Autonomous data quality monitoring

Anodot’s machine learning capabilities make it a completely autonomous solution. There’s no need to define what data to look for or when, no manual thresholds to set up or update. Anodot’s adaptive alert dashboard is easily used to create advanced data quality monitors. The system’s alert reduction mechanism ensures that you can leave alert storms, false positives, and unidentified incidents behind.