I Have GCP, Why Do I Need Dataiku?
Discover the synergy between Google Cloud Platform and Dataiku. Empower your teams, streamline ops, and future-proof your AI initiatives.
READ THE BLOGDataiku’s end-to-end data science platform deployed with Google Cloud and integrated into Google Cloud services enables organizations of any size to deliver enterprise AI in a highly scalable, robust, and collaborative environment.
“Collaboration is really important. If we’re just a team with everyone running their own notebooks on their own machines, you can’t say ‘hey check out this thing I did a few weeks ago.’ With the power of Dataiku and GCP, we can work on projects at the same time in a way we couldn’t do before.”
— Ben Powis, Head of Data Science at MandM Direct
Connect, visualize, transform, and analyze datasets through native connections to:
Scale data pipelines and machine learning processes by leveraging GCP’s compute
Leverage Google’s AI and visualization services
See how MandM Direct uses Dataiku and Google Cloud Platform (GCP) to build and maintain a data science practice that operationalizes 10x more models versus a code-only approach.
READ THE STORYDiscover the synergy between Google Cloud Platform and Dataiku. Empower your teams, streamline ops, and future-proof your AI initiatives.
READ THE BLOGCombine Snowflake’s highly scalable computational power and processing flexibility with Dataiku’s machine learning and model management capabilities.
LEARN MOREDataiku and Microsoft empower everyone - not just expert data scientists and engineers - to create, deploy, and manage AI-driven data projects at scale.
LEARN MORETurbo-charge AI initiatives with Dataiku and AWS, enabling hundreds of data workers to benefit from the scalability and the broad variety of services that AWS provides.
LEARN MOREA composite organization in the commissioned study conducted by Forrester Consulting on behalf of Dataiku saw the following benefits:
reduction in time spent on data analysis, extraction, and preparation.
reduction in time spent on model lifecycle activities (training, deployment, and monitoring).
return on investment
net present value over three years.