Ensuring data quality is essential for analytics, data science and machine learning. Superconductive's Great Expectations open source framework wants to do for data quality what test-driven development did for software quality
Technical debt is a well-known concept in software development. It's what happens when unclear or forgotten assumptions are buried inside a complex, interconnected codebase, and it leads to poor software quality. The same thing also applies to data pipelines, it's called pipeline debt, and it's time we did something about it.
That's the gist of what motivated Abe Gong and James Campbell to start Great Expectations in 2018. Great Expectations is an open-source tool that aims to make it easier to test data pipelines, and therefore increase data quality.
Superconductive, the force behind Great Expectations, has announced it has received $21 million in Series A funding led by Index Ventures with CRV and Root Ventures participating. We caught up with Gong to learn more about Great Expectations.
Article published on ZDNet)
