Introducing Metadata Metrics: instant data observability for your entire data warehouse

Meet Metadata Metrics—instant coverage for your entire data warehouse so you can quickly detect the most common data quality issues. Metadata Metrics work by scanning your existing query logs to automatically track key operational metrics including hours since the last table load, rows inserted, and the number of read queries on every dataset. Metadata Metrics take minutes to set up, with zero manual configuration and almost no additional load to your warehouse.

Among data observability solutions, Bigeye is the only platform capable of broadly monitoring across tables and deeply into the most critical datasets, reducing the number of expensive outages affecting business-critical applications.

Instant observability for your entire warehouse

Metadata Metrics give you instant insight into key operational attributes of every table in your warehouse including:

1. Time since the table was last refreshed
2. Number of rows inserted per day
3. Number of queries run per day

With Metadata Metrics enabled, your team will be the first to know about stale data, table updates that are too big or too small, or changes in table utilization thanks to Bigeye’s best-in-class, anomaly detection system. Also, if you have data exchange software in your stack, metadata metrics can feed into those analytics without altering the inherent meaning that transpired during data acquisition.

T-Shaped Monitoring—wide and deep

Bigeye is the creator of T-shaped Monitoring, a unique approach to data observability that tracks fundamentals across all your data while applying deeper monitoring on the most critical datasets such as those used for financial planning, machine learning models, and executive-level dashboards. This approach ensures you're covered against even the unknown unknowns.

Here’s how it works:

1. Enable Metadata Metrics to instantly track the basics across all your data.
2. Go deep on each business-critical dataset using a blend of metrics that Bigeye suggests for each table from its library of 70+ pre-built data quality metrics.
3. Take it even further by adding custom metrics with templates and virtual tables to ensure custom business logic is being monitored for defects.

T-Shaped Monitoring gives data teams peace of mind with monitoring across your entire warehouse, 24/7. With Metadata Metrics, it’s even faster to set up and deploy broad coverage without the hassle of configuration. Ensure your business is never disrupted. Detect both simple problems, such as stale data, and even the most subtle errors in any critical dataset.

Metadata Metrics are available to all customers now. To learn more, read our documentation about Metadata Metrics. Or, if you’re ready to see it, we’d love to give you a demo.