Its greatest strength is enabling true collaboration between data experts and business teams on a single platform. It seamlessly bridges technical work like coding and ML engineering with visual and no-code interfaces. This breaks down silos, accelerates project delivery and ensures AI solutions are built with crucial business context, making them more impactful and sustainable. Review collected by and hosted on G2.com.

For smaller teams or simpler projects, Dataiku will be premium. The platform's extensive features come with inherent complexity, which can lead to a steeper learning curve. Its pricing model is often seen as enterprise-focused, potentially making it less accessible for startups or individual users who don't need its full collaborative scale. Review collected by and hosted on G2.com.

I like how Dataiku helps us identify some data quality issues and correct them before presentation. It's really important because, without data quality, the data is almost worthless, and you can't really make any insight out of it if it's not good quality. I also found the setup process to be very easy. We integrated with our intra authentication system, set up connections to Snowflake, and then started working on it. Review collected by and hosted on G2.com.

It's the ability to actually be able to extract data, look at it, evaluate, transform it, and present it. Review collected by and hosted on G2.com.

What I like most about Dataiku is the way it balances ease of use with strong analytics and AI capabilities. It allows business users, analysts, and data scientists to collaborate smoothly within the same platform. The combination of visual workflows and the flexibility to code when needed makes it straightforward to go from experimentation to production more quickly. Review collected by and hosted on G2.com.

One thing I dislike about Dataiku is that it can feel bulky and resource-heavy at times.

It tends to save/cache data in many places, which can make workflows harder to manage and slower to navigate.

For hardcore technical teams that prefer lightweight, code-first tooling, it may feel slower and more restrictive than working directly with native engineering stacks. Review collected by and hosted on G2.com.

I really like the Orchestrator level, as it helps with my tasks. The UI is another aspect that I find valuable, especially for various use cases. Dataiku is also helpful in AI governance, agent traces, and token aspects. Additionally, I appreciate the model evaluation and prompt monitoring features, which make my workflow more efficient. Review collected by and hosted on G2.com.

The UI can be improved with more integration. Review collected by and hosted on G2.com.

The simplicity to analyse data, results, and the gain of time compared to doing all that in python in a classic IDE Review collected by and hosted on G2.com.

Recently I did not like how difficult and long it was to add input files in managed folders. I could not upload subfolemders for exemple. Also multiple times when I uploaded large number of files, some were not uploaded. Review collected by and hosted on G2.com.

I like that Dataiku lets me handle data projects and build machine learning models by pulling in data from different sources, cleaning and organizing it, and experimenting with models all in one place. The combination of a visual interface with coding options makes it accessible for both technical and non-technical team members, smoothing out data project management. I love how it reduces repetitive tasks, decreases mistakes, and keeps complex projects organized and running smoothly. It's great that everyone on the team can contribute, no matter their technical skills, making data work easier and less stressful. Review collected by and hosted on G2.com.

One thing I’ve noticed about Dataiku is that it can feel a bit overwhelming at first because there are so many features and options. Working with really large datasets or complex workflows can sometimes be a little slow. I also think it could be a bit easier for new users to get started. Overall, it’s a great tool, but a little more guidance and smoother performance would make it even better. Review collected by and hosted on G2.com.

The low code environment and workflow creation plus ease of use Review collected by and hosted on G2.com.

There nothing o can think of that I dislike Review collected by and hosted on G2.com.

I really appreciate how the graphical user interface handles paths and threads. It allows you to manage all your code and datasets visually, and everything is automatically aligned, which makes the experience very soothing to use. Review collected by and hosted on G2.com.

There isn't anything in particular that I dislike about Dataiku. However, one area for improvement would be better management of the history and recent code I've worked on. It would be helpful if this information were more easily accessible and visually highlighted. Review collected by and hosted on G2.com.

low-code option that is visually appealing that has easy collaboration between various teams of different technical levels Review collected by and hosted on G2.com.

it takes a while to get used to the UI and find due to some auto documentation can be misleading Review collected by and hosted on G2.com.

I really like probably seeing the flow visually with Dataiku. It's helpful having the visual recipes too if I don't wanna write code. Review collected by and hosted on G2.com.

The coding pilot doesn't work for me. I don't know if that's just a Boeing restriction that we don't have it activated. So I have to go to a third party AI tool if I wanna use the coding agent. Review collected by and hosted on G2.com.