Bigeye Combines Enterprise-Grade Lineage Tech with Observability for Reliable Data Analytics

Bigeye, the developers of the data observability platform designed for data people, by data people, is announcing the availability of Bigeye Dependency Driven Monitoring, an addition to the Bigeye data observability platform that empowers business leaders to trust the data fueling their dashboards. Enabling enterprise data teams to connect their analytics dashboards, map every dependency for both modern and legacy data sources, and deploy targeted data observability, Bigeye Dependency Driven Monitoring allows organizations to depend on reliable data analytics.

“We’ve spoken with hundreds of enterprise data leaders and, despite investing heavily in data quality tools and processes, they still struggle to deliver reliable data analytics to business users,” explained Kyle Kirwan, CEO and co-founder of Bigeye. “Something the data observability industry hasn’t yet solved is how to handle the complexity and size of large enterprise data pipelines. This is because enterprise dashboards have a long list of dependencies that span modern and legacy technologies and data observability platforms have yet to offer true support for the types of hybrid environments nearly all Fortune 500 companies have.”

To solve this issue, Bigeye Dependency Driven Monitoring leverages enterprise-grade lineage technology—paired with its data observability functionality—to automatically track the entire enterprise data pipeline with column-level precision, even if the pipeline includes a plethora of legacy data technologies.

“Our competitors often only support limited lineage for things like Snowflake, Databricks, or BigQuery, and lose track upstream from there. Without gathering full lineage, they force customers to choose between over-monitoring their pipeline—which wastes compute and creates alert noise—or risking a data outage by trying to guess which columns are important,” said Kirwan. “Bigeye Dependency Driven Monitoring figures out the exact data your analytics actually relies on and efficiently deploys monitoring on just those columns.”

Column-level specificity enables data engineers to move past broad, blanket monitoring and instead deploy data observability only on the columns that matter. This not only lowers compute costs and accelerates time-to-value, it also reduces alert noise and additional overhead through unnecessary monitoring, according to Bigeye.

By monitoring the entire lineage chain from the dashboard to the original data source, Bigeye Dependency Driven Monitoring increases the chance that any issue is caught earlier in the pipeline journey. Additionally, Bigeye’s anomaly detection system learns “the trend, variance, seasonality, and other factors of each attribute of our customer’s data in order to alert when it sees something abnormal happening. The models learn from customer feedback as well, so they can adapt to changes in the data without needing manual editing,” according to Kirwan.

Bigeye Dependency Driven Monitoring is fueled by Bigeye Lineage Plus, a complete data lineage technology built to handle the largest, most complex enterprise pipelines. With 50 connectors that span both modern and legacy enterprise data sources, support for cloud and on-prem infrastructure, and ETL job information capture, Bigeye Lineage Plus offers the unique ability to maintain column-level precision across enterprise data technologies.

To learn more about Bigeye, please visit