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HomeTechBigeye Introduces End-to-End Enterprise Lineage for Hybrid Data Environments

Bigeye Introduces End-to-End Enterprise Lineage for Hybrid Data Environments

Bigeye is the first data observability company to provide end-to-end, column-level coverage across cloud data warehouses and on-premises data sources.

When data issues arise, Bigeye will use its Scorecard feature to summarize and present them either alongside the dashboards or directly within the product.

Bigeye now automatically maps end-to-end lineage for analytics dashboards across cloud data warehouses, ETL tools, and legacy data sources.

Many enterprises we meet really struggle with lineage. Unfortunately there are a number of platforms out there that claim to do lineage but the level of actual automation is pretty limited.”

— Kyle Kirwan, Bigeye CEO

SAN FRANCISCO , CALIFORNIA, USA, June 5, 2024 /EINPresswire.com/ — Today, Bigeye announced the launch of its new column-level lineage support for ETL platforms, including the availability of Informatica Powercenter lineage, enhancing data observability across hybrid enterprise data environments. This new feature allows customers with on-premises legacy data sources to use Bigeye’s data observability platform to map the lineage of their entire data analytics pipeline—even as data moves between on-premises sources and their cloud data warehouse—delivering comprehensive data quality insights to data consumers.

Bigeye is the first data observability company to provide end-to-end, column-level coverage across cloud data warehouses and on-premises data sources, extending through to analytics dashboards. This is made possible through the integration of over 50 Bigeye Lineage Plus Connectors for transactional databases, data lakes, ETL platforms, analytics tools, and more.

Speaking on their new features at Snowflake Summit, Bigeye CEO Kyle Kirwan said, “Many enterprises we meet really struggle with lineage. Unfortunately there are a number of platforms out there that claim to do lineage but the level of actual automation is pretty limited, which creates gaps in the lineage graph. Our new Lineage Plus connectors for ETL platforms close a key gap, keeping the lineage trace unbroken between source transactional databases and data lakes or warehouses.”

Once the complete hybrid data pipeline is mapped, business users and data analysts can easily deploy targeted monitoring on specific tables and columns, ensuring every dependency powering their analytics dashboards is covered. When data issues arise, Bigeye will use its Scorecard feature to summarize and present them either alongside the dashboards or directly within the product.

Bigeye hosted two break-out sessions at Snowflake Summit, “Data and Analytics Leaders Roundtable: Ensuring Trust in Enterprise Analytics,” and “Bigeye: Making Analytics Trustworthy by Default,” on Monday, June 3rd and Wednesday, June 5, respectively.

Snowflake Summit attendees are invited to visit Bigeye at booth 1302 to experience a live demo of Bigeye’s new ETL lineage capabilities with Informatica Powercenter and discuss how Bigeye can enhance data reliability within their organizations.

Bigeye will also be at Databricks showcasing how Fortune 1000 companies use Bigeye to deliver accurate, reliable data without interruption at booth 94. Databricks attendees can join our talk, “Bigeye: Making Analytics Trustworthy by Default,” on Tuesday, June 11th from 11:30 AM – 11:50 AM PDT.

About Bigeye:

Bigeye is the enterprise-grade data observability platform 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-prem, in the cloud, or hybrid. Visit our website to learn more more or request a demo.

Eleanor Treharne-Jones
Bigeye
+1 415-430-8945
email us here

Originally published at https://www.einpresswire.com/article/717188191/bigeye-introduces-end-to-end-enterprise-lineage-for-hybrid-data-environments

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