Bigeye Introduces New ‘Metadata Metrics’ Observability Solution

Data observability platform provider Bigeye introduced a new product this week, Metadata Metrics.

Bigeye says it provides instant data observability for an entire data warehouse allowing for fast detection of data quality issues.

Metadata is an essential part of data warehousing, as it is data that gives insight into the contents and processes of a data warehouse and is used for its management and maintenance. More specifically, Bigeye mentions its Metadata Metrics solution can give insights into operational attributes of tables, including time since the table was last refreshed, number of rows inserted per day, and number of queries run per day. Bigeye’s anomaly detection system, enabled with Metadata Metrics, allows for the detection of stale data, table updates that are too big or small, and changes in table utilization.

“Metadata Metrics scans existing query logs to automatically track key operational metrics, including the time since tables were last loaded, the number of rows inserted, and the number of read queries run on every dataset. Metadata Metrics takes only minutes to set up, with zero manual configuration and almost no additional load to the warehouse,” the company stated in a press release.

Metadata is a rapidly growing element in data warehouse management that observability platforms aim to assist enterprises with taming. As business applications become larger and more complex, IT and data professionals can use insights from warehouse metadata in order to detect and amend problems within their applications. Bigeye claims to be the only platform capable of broadly monitoring across tables and deeply into the most critical datasets, reducing the number of expensive outages affecting these business-critical applications.

A graphic demonstrating Bigeye’s T-shaped Monitoring concept. Source: Bigeye

In a blog post discussing the new product, Bigeye CEO and co-founder Kyle Kirwin explains the company’s signature T-shaped Monitoring, or wide and deep monitoring, which he says is “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.” He says customers who enable Metadata Metrics can do a deep dive into a dataset with the product’s blend of suggested metrics for each table from a library of more than 70 pre-built data quality metrics. They can then go further by adding their own custom metrics with templates and virtual tables.

“We built Metadata Metrics so our customers can detect basic operational failures anywhere in their warehouses without lifting a finger,” said Kirwan. “Bigeye could already do deeper monitoring for our customers’ most critical tables better than any other platform. Now, we can also go really wide and monitor the basics on thousands of tables for them, instantly.”

Metadata Metrics is now available to all existing Bigeye customers. For more information on available pre-built metrics, read the technical documentation at this link.

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