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Data lakes are notoriously complex. For data engineers who battle to build and scale highqualitydata workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.
Current open-source frameworks like YAML-based Soda Core, Python-based Great Expectations, and dbt SQL are frameworks to help speed up the creation of dataquality tests. They are all in the realm of software, domain-specific language to help you write dataquality tests.
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