I think Dataiku could be improved or enhanced in future releases with more 'talk to my data' capabilities, maybe more NLP features, and maybe a platform to build agents.

These improvements would benefit me and my processes because they will help us to continue using Dataiku as one platform; right now we are exploring other platforms for the features which are missing, and if they are available within the same platform, I think it will increase the usage of Dataiku further.

I think the pricing and licensing of Dataiku is a bit expensive; it could be improved further, and I think they should have a different kind of licensing model as well.

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I do not see anything that I would improve or enhance in Dataiku at this time; overall, it is a good tool to incorporate and to suggest to customers.

Currently, I do not see anything specific that I would include or any functionality that requires enhancement. Dataiku gives the complete picture of the AI universe, and we have not faced any glitches, so I do not have recommendations or suggestions for improvement.

All products have room for improvement, and I would like to see their pricing simplified, as it is somewhat complex. In terms of documentation, there is substantial documentation available. Customer support is good, the product is scalable, and it provides flexibility to develop. Someone who needs to do coding can do it, and someone who does not know coding can also build solutions, but the pricing is complex, which I believe should be improved.

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One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues.

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I need more experience in the sector, which is health. The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience.

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In terms of enhancing collaboration within my team, I would not say Dataiku is the best one because it's so expensive. We are not able to provide it to everyone. There are very few people who have the developer license and are using it. Once the data pipeline is created, then we are directly handing over that data pipeline to our user on the ingestion layer. It is not a very cost-effective solution, I must say, though it is good for developing purposes only.

Pricing can be improved.

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There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend it by developing and integrating custom components easily with existing ones.

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Dataiku's pricing is very high, and commercial transparency is a challenge. Support is also an area needing improvement. More features like LLM security, holographic encryption, and enhanced GPU integration would be beneficial. View full review »

To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is possible for a preprocessing step. Visualization and integration are the main areas I would like to see enhanced.

In my experience, Dataiku can be more stable.

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One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub.

Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.

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The no-code/low-code aspect, where DataRobot doesn't need much coding at all. 

Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku because you still have to code and use either Python or R, or Scala. However, with DataRobot, you don't have to do that at all.

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I think it would help if Data Science Studio added some more features and improved the data model.

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When the flows get complex, there are too many data sets on them. Normal users will get confused by the influx of information. This was a problem up until recently, however, they have since resolved it. Now, there's a feature called Zones(introduced in version 8) that allows users to collapse multiple flows into a single flow. It allows everyone to easily carry on with their work.

Other than that issue, that has now been resolved, there isn't anything lacking by way of features.

The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective.

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From an administrative point of view, I would like to be able to communicate with the users who are logged into the system. For example, I would like to be able to send a broadcast message that says "I am shutting down the system."

I would like to see more organization and better cohesion within the tool.

In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin.

I would like to have a better way to manage images and sound.

The error messages are not self explanatory and can sometimes be difficult to understand.

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I think the interface is very nice, but for somebody who is not as familiar with IT as I am, it may be much more difficult for them. It is nice for me because I'm familiar with this type of software that falls in the realm of the data science platform. I can see how a client who really doesn't know anything about IT or computers might try to use it and find that it would be a little difficult to access some features. That type of user may really need training in order to work with Dataiku. So, in the next release of Dataiku DSS (Data Science Studio), they should make it more friendly for everybody to use, not just IT people. 

For me, I find that it is a little slow during use. When I use Dataiku to run my script to transfer data, it takes more time than I would expect for the operation to complete.

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I would like to have better exclusion of data capability.

The ability to have charts right from the explorer would be an improvement.

I would like to see additions to the architecture for specific business use cases.

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Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable.

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