At Great Expectations, we’re building an end-to-end solution for your data quality process. And that solution—the GX platform—has two components: GX Cloud and GX Core.
GX Core, our open source library, is the world’s most popular data quality framework. It has hundreds of contributors, thousands of customer deployments across many industries and geographies, and millions of downloads every month.
GX Core provides the platform’s technical data quality capabilities. The biggest of these is, of course, Expectations—the clear, intuitive way in which GX implements data quality tests. And as an open source Python framework, GX Core gives data teams a lot of flexibility and control, which is one reason that it’s so popular.
Obviously, the technical implementation of Expectations alone is a critical part of our platform, not to mention all of the other capabilities that GX Core provides. This criticality illustrates exactly why we’re committed to developing, advancing, and maintaining GX Core in the future. Without GX Core, there’s no GX platform at all.
But a complete, end-to-end data quality solution needs more than just the technical capabilities of connecting to data, running tests, and displaying results—no matter how effective or expressive those capabilities might be!
To effectively implement a data quality process, you need infrastructure to host it. You need a way for nontechnical stakeholders to interact with it. You need a place for data teams and stakeholders to record their joint decisions about the appropriate tests and expected qualities of the data.
You need a way to automate your tests, and a way to be notified when your tests find something significant. You need tools to view your results and store your historical data. In many scenarios, you need access controls to ensure that only approved people can edit or even access the tests.
None of those things are part of GX Core.
In the past, GX Core users had to create those capabilities for themselves, using additional tools, custom development, or both—and they did! That option is still on the table for teams who want it.
But our goal with the GX platform is to provide a complete solution. Something that a data team can pick up and start using immediately, with everything they need ready to go. Data teams are busy, and we want to empower them to focus all their energies on understanding their data, implementing tests, and resolving issues.
GX Cloud is the component of the GX platform that makes it easy to harness the powers of GX Core.
GX Cloud contributes by providing a fully hosted SaaS infrastructure, so startup is just a matter of creating an online account. It’s quick and easy.
Once you’re logged in, its intuitive user interface is accessible to everyone: data teams to nontechnical stakeholders. This not only centralizes collaborative work—work which is crucial to an effective data quality process—but makes it significantly more straightforward and easier for busy stakeholders to meaningfully engage with data quality efforts.
Plus that interface enables a whole suite of additional features that support your data quality process: in-app scheduling, configurable notifications, historical results charts, in-context notes and changelog, and role-based access controls, among other things.
By using GX Cloud, data teams can get the power of Expectations and GX Core, plus start-to-finish support for the rest of their data quality process.
If you’re an analogies person, think of the GX platform as a car. GX Core is the engine: a powerful machine, but it needs additional components to help you get anywhere. GX Cloud is the rest of the car: everything you need to actually go places, and harnessing the engine’s power to make it happen.
Try GX Cloud, now in public preview.
Try GX Core on GitHub or Pypi.
