G2

Rythm G.

Marketing Team Head

Small-Business (50 or fewer emp.)

8/31/2026

"All-in-One Data Science Platform That Streamlines Workflows and Collaboration"

5/5

What do you like best about Dataiku?

What I like most about Dataiku is that it combines data preparation, analysis, visualization, and machine learning in a single platform. The visual workflow makes it easy to build and follow data pipelines without needing to write code for every step, while still offering flexibility for people who prefer working in Python or SQL. I also find its integrations with different data sources helpful, and the interface makes it straightforward to collaborate with others and share workflows. Overall, it streamlines the data science process and reduces the need to switch between multiple tools. Review collected by and hosted on G2.com.

What do you dislike about Dataiku?

One area that could be improved is the learning curve for some of the more advanced features. Although the visual interface is helpful, it can still take new users a while to understand how the different components and workflows fit together. Some of the advanced integrations and AI features would also benefit from clearer documentation, along with more beginner-friendly examples that show how to use them in practice. Performance can occasionally vary depending on the complexity and size of a workflow, so more guidance on optimizing larger projects would be useful as well. Review collected by and hosted on G2.com.

What problems is Dataiku solving and how is that benefiting you?

Dataiku simplifies the end-to-end data science workflow by bringing data preparation, analysis, visualization, and machine learning into a single environment. Rather than switching between multiple tools at different stages of a project, I can keep workflows and experiments organized in one place. The visual interface is especially helpful for quickly exploring data and building workflows, and the option to use Python or SQL adds flexibility when I need more advanced analysis. Overall, it’s easier to experiment, reproduce workflows, and collaborate on data-driven projects. Review collected by and hosted on G2.com.