Dataiku and SQream: A Powerful Combination for Big Data Analytics

If you are a data scientist or an engineer who deals with big data, you know how challenging it can be to process, analyze, and derive insights and predictions from massive amounts of data. You need a fast, scalable, and reliable data platform that can handle complex data preparation pipelines and deliver results in minutes, not hours or days. Nevertheless, it can’t work without an end-to-end AI platform that allows you to develop, govern, and maintain ML models.   

That’s why we are excited to announce that Dataiku, the leading AI and machine learning platform, has a new integration with SQream, the GPU-accelerated data processing and analytics platform. This integration allows you as a Dataiku user to read from and write data into SQream, enabling you to leverage the power of both platforms for your big data ML and analytics projects.

By using the Dataiku integration with SQream, you can enjoy the following benefits:

– You can easily connect to SQream from Dataiku and access your data with a few clicks. You don’t need to install any drivers or configure any settings.

– You can use Dataiku’s visual interface to explore, prepare, and transform your data in SQream. You can also use Dataiku’s code recipes to write custom SQL queries or use other languages such as Python or R.

– You can prepare vast amounts of data easily at a terabytes-to-petabytes scale and boost your numerous ETL processes.  

– You can use Dataiku’s advanced features to build, test, and deploy machine learning models using your data in SQream. You can also use Dataiku’s scenarios and automation tools to orchestrate your workflows and monitor your projects.

If you want to try out Dataiku and SQream together, you can explore the new Dataiku release notes (version 12.3.2).