Bigeye Releases Deltas to Automatically Compare and Validate Datasets in Seconds

New solution brings greater reliability to data replication, cloud migration, and promoting data from staging to production.

SAN FRANCISCO--(BUSINESS WIRE)--Bigeye, the creator of the leading data observability platform, today announced the release of Deltas, an industry-first solution that automatically compares and validates multiple versions of any dataset in seconds. Whether replicating data into a data warehouse, migrating from one cloud to another, or getting ready to promote data from staging to production, Deltas provides greater reliability in a fraction of the time.

When moving data, all sorts of issues can occur, including delayed ingestion, dropped or duplicated records, and mutated values. These issues impact data quality, slow down projects, and erode trust. Comparing datasets is a crucial step for many data engineering projects, but it’s often difficult and time-consuming due to the need for custom SQL queries, complex and brittle spreadsheets, or bespoke Python scripts. Deltas extends Bigeye’s best-in-class data observability platform, making it easy to map a source and target, intelligently apply data quality metrics, and detect drift and discrepancies fast.

“Udacity has a strong data culture, and we have hundreds of datasets with new additions and enhancements released weekly. The ability to automatically compare datasets before promoting them to production allows our team to apply software engineering best practices, have greater confidence in our data, catch issues we would otherwise miss, and speed up our development process,” said Simon Dong, head of data engineering at Udacity.

Bigeye users can now identify discrepancies between even complex datasets in seconds. Deltas uses Bigeye’s at-runtime query generation to apply the same observability configuration to both datasets, regardless of the SQL dialects of their sources, and detects for differences between them. With Deltas, customers have confidence in knowing they’ll be alerted to any issues that occur when moving data from A to B.

“We architected Bigeye to be an extensible framework, which allows us to apply data observability to all kinds of exciting use cases. We started by enabling data teams to automatically detect data quality and data pipeline issues. Now with Deltas, customers can easily compare and validate datasets,” said Egor Gryaznov, CTO and co-founder at Bigeye. “We look forward to enabling more groundbreaking user workflows through data observability in the near future.”

Learn more about Deltas’ powerful comparison and validation capabilities:

• See how Deltas works on our product page.
• Check out our blog to learn more about the challenges Deltas solves.

About Bigeye

Bigeye is a data observability platform that brings data engineers, analysts, scientists, and stakeholders together to build trust in data. Companies like Instacart, Clubhouse, and Udacity use Bigeye to automate monitoring and anomaly detection and create SLAs to ensure data quality and reliable data pipelines. With complete API access, a user-friendly interface, and automated yet flexible customization, data teams can monitor quality, proactively detect and resolve issues, and ensure that every user can rely on the data. www.bigeye.com