Faster and better ML data preparation with SQream

With the ever-growing complexity of Machine Learning (ML) models, the need for ML Operations (MLOps) has become essential in deploying successful models into production and continuously improving them with new data.

On average, data scientists spend 80% of their time preparing data. Attempts to deal with this challenge, such as training smaller datasets or conducting fewer cycles of experimentation after deployment, only reduced ML models’ accuracy and forced companies to compromise.