Users get frustrated when their data products break or data assets are not accurate. More often than not, breakages happen due to data quality issues such as delays, duplication, missing or malformed data, or data containing outliers. And these issues can affect a model, a dashboard, or even an entire application.
Data engineering teams, on the other hand, manage rapidly evolving data from a variety of internal and external sources, with data being transformed at multiple steps, often at the scale of hundreds or even thousands of tables. Bigeye is designed to make it easy for data teams to identify and resolve data quality problems proactively before something breaks and before end-users are affected.