A data bug refers to an error or flaw in a dataset. If left unaddressed, data bugs significantly affect a model’s predictions or outcomes, which may be either favorable or unfavorable to the developer.
Data bugs are often hidden and hard to detect, taking into account the following:
Data bugs may remain undiscovered for a long time, leading to inaccurate results that cause enterprises to make faulty decisions and incur high expenses. Fortunately, there are two ways to address data bugs:
Real-world data is messy, and data bugs will be inevitable. But with iteration and continuous data quality improvement, they don’t have to bog down your machine learning projects. Keep track of fixes made to your datasets with Pachyderm and its best-in-class version control and data lineage features. Sign up for a free trial today to ease your team’s debugging issues.« Back to Glossary Index