80% of a data engineer's time is spent on grooming datasets to be useful for data science uses.
With organizations, you can save time creating, cleaning, and publishing datasets by up to 10x while being interoperable with any cloud provider or external tool. Star datasets you like to quickly iterate experiments across your data science organization.
Our storage cost model uses a cold/hot storage approach to save you money.
This results to up to 3-5x cost savings for data storage relative to other platforms.
Let's be real - most data is just noise and can't be replicated.
Survey protocols and methods for data collection increase data quality and provide the ability to audit and replicate results.
Our organizations allow for quick setup of groups to share datasets.
We provide fine-tuned role-based and audit log access through API tokens and user roles (e.g. billing, general, or admin users), allowing for quick compliance with GDPR, HIPAA, and similar regulations.
We try to make data engineering enjoyable.
With features like a GitHub-like contribution graph interface and badges to reward large-contributors, we try to make the process of generating and maintaining datasets fun - and contribute to tutorials to train the next-generation of data engineers.