Bigeye Dependency Driven Monitoring Ensures Reliable Analytics
Bigeye Dependency Driven Monitoring combines enterprise-grade lineage technology with data observability to automatically trace the entire enterprise data pipeline at column-level precision.
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Bigeye has released Bigeye Dependency Driven Monitoring. The data observability platform allows enterprise data teams to connect their analytics dashboards, map every dependency across modern and legacy data sources, and deploy targeted data observability to ensure they stay reliable by default.
According to Bigeye's 2023 State of Data Quality Report, 70% of business leaders don't trust analytics dashboards to make critical decisions due to regular data quality incidents. Kyle Kirwan, CEO and co-founder of Bigeye, said, "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.
“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."
Bigeye Dependency Driven Monitoring uniquely solves this challenge by combining enterprise-grade lineage technology with data observability to automatically trace the entire enterprise data pipeline at column-level precision through traditional and modern technologies, ETL stages, and even across the boundary from cloud to on-premises environments.
Improves Data Observability ROI
Without a clear understanding of which columns are critical dependencies for business operations and which are not, data engineering teams must deploy broad, blanket monitoring across a large number of tables and columns to reach adequate coverage. Although this approach helps engineers identify anomalies anywhere they occur in the data environment, it also requires them to manage higher compute costs, unwanted alert noise, and additional overhead as a result of deploying unnecessary monitoring.
Bigeye Dependency Driven Monitoring turns this paradigm on its head by allowing data analysts and business users to start from their critical dashboard and—in just a few clicks—enable data observability on each column that matters and none that don't.
When compared with other data observability approaches, Bigeye Dependency Driven Monitoring:
- Accelerates time to value and improves trust for data consumers
- Offers clear visibility into the health of the entire analytics data pipeline for analysts
- Reduces alert noise and enables faster issue resolution for data engineers.
- Lowers total cost of ownership and reduces computational resource overhead for data leaders
When a data issue is detected, Bigeye will instantly notify each data source owner impacted through Slack or Microsoft Teams. Bigeye can also automatically create a bi-directional ticket in ITSM tools such as JIRA and ServiceNow for integrated incident management.
For data consumers, Bigeye will display data health updates directly in their analytics dashboard, providing instant insight into whether their analytics is reliable. Data engineering teams can then use Bigeye's lineage-powered root-cause and impact analysis to quickly trace the data problem to the source for fast triage and resolution.
Powered by Bigeye Lineage Plus
Data lineage has become a ubiquitous feature for many types of data operations tools. Due to the complexity of mapping lineage in legacy or on-premises environments, most tools require the customer to use complex, custom APIs or manual entry to try and capture a full picture of an enterprise pipeline.
Bigeye Dependency Driven Monitoring is powered by Bigeye Lineage Plus, a data lineage technology built to handle large, complex enterprise pipelines. Bigeye Lineage Plus includes 50 connectors for transactional databases, cloud data warehouses, data lakes, ETL platforms, analytics tools, and more. Each connector includes parsers that trace lineage at the column level even as it moves from cloud to on-premises sources. As a result, data analysts and data engineers can view a single lineage map of their entire pipeline all the way through to an analytics dashboard or data product.
About Bigeye
Bigeye is enterprise-grade data observability for modern and legacy data stacks. Bigeye brings together data observability, end-to-end lineage, and scalability and security to give enterprise data teams unmatched insight into the reliability of data powering their business—no matter if it's on-premises, in the cloud, or hybrid.