DQL: SQL for unstructured data
Query, organize, cleanse, and instantiate data objects with Iterative's custom data query language (DQL), built for unstructured data and machine learning use cases.
Use a first-of-its-kind query language to search and manage annotations and meta information. Manipulate your ML data quickly and efficiently to get the correct data for improving your models.
Flexible data set creation
Create data sets based on specific annotations instantly. Programmatically label and create signals for your data sets. Version these data sets as you develop your model, using data sources from any cloud location.
Use auxiliary features (i.e., files attributes, JSONs, helper ML models, and more), indexed by DVC-Cloud, to create the right data set for your models. Do this across any cloud or data source.
Search across all data sets with unstructured data catalog
Find the data set you're looking for across any cloud, with full details around lineage and use. Then use meta information to create custom data sets that can be shared and used across your team.
Quickly search across any cloud and see context around who's used the data set last, where it's stored, how it's used, and more. Eliminate the need for custom scripts and long waits asking team members how a data set was changed. All in a single place.
Start managing your unstructured data now
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