I consider these kinds to be 'full-fledged data quality frameworks.' They can be either open source (such as Great Expectations and Soda) or paid (like MonteCarlo and Bigeye). Thus, they go beyond mere libraries with functions to install and use. That being said, I find Great Expectations to be quite heavy, with many dependencies even for smaller tasks-I would definitely recommend giving Soda.io a try! :)
What's your go-to Python Library for data engineering?
What are your opinions on great expectations library for data validation?
I consider these kinds to be 'full-fledged data quality frameworks.' They can be either open source (such as Great Expectations and Soda) or paid (like MonteCarlo and Bigeye). Thus, they go beyond mere libraries with functions to install and use. That being said, I find Great Expectations to be quite heavy, with many dependencies even for smaller tasks-I would definitely recommend giving Soda.io a try! :)