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Maintaining data quality doesn’t have to be hard. GX Cloud is now in public preview: try it today and see value in minutes. Great Expectations is a powerful platform that's revolutionizing data quality and collaboration. Find out why companies around the world are choosing GX.
Nov 2, 2021 · Automated data profiling. Great Expectations can also profile your data automatically and based on results generate the expectations based on profiling.
GX OSS is a data quality platform designed by and for data engineers. It helps you surface issues quickly and clearly while also making it easier to collaborate with nontechnical stakeholders. Its powerful technical tools start with Expectations: expressive and extensible unit tests for your data.
Oct 15, 2021 · In this article you created a first local deployment of the Great Expectations framework for data validation. You initialized a Great Expectations Data Context, created a new file-based Datasource, and automatically generated an Expectation Suite using the built-in profiler.
Feb 4, 2021 · Feb 4, 2021. What is Great Expectations? Great Expectations is a useful tool to profile, validate, and document data. It helps to maintain the quality of data throughout a data workflow...
Dec 27, 2015 · Great Expectations can be used with your existing data assets - it is able to use different backends such as SQL databases, Spark clusters, or just your plain old filesystem. It will execute...
Feb 23, 2022 · As an open source library, Great Expectations fills the need for a shared standard for data quality by providing two things: a wide variety of data validation rules (called Expectations) that define an open, shared standard for data quality and express it in software
A powerful, flexible data quality solution. Profile, test, and document with an open source platform developed by data engineers, for data engineers. Get started with GX OSS. Looking for a Cloud solution? Learn more. Have confidence in your data. Get started quickly.
Use this quickstart to install GX OSS, connect to sample data, build your first Expectation, validate data, and review the validation results. This is a great place to start if you're new to GX OSS and aren't sure if it's the right solution for you or your organization.
Key Features. Expectations are assertions about your data. In Great Expectations, those assertions are expressed in a declarative language in the form of simple, human-readable Python methods. For example, in order to assert that you want the column “passenger_count” to be between 1 and 6, you can say: Python. expect_column_values_to_be_between(
