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.
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.
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.
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.
Business Intelligence Developer/ Data Scientist at a tech services company with 11-50 employees
Real User
2019-12-04T05:40:00Z
Dec 4, 2019
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.
Practice Manager Data Intelligence at a tech services company with 1,001-5,000 employees
Real User
2019-11-13T05:29:00Z
Nov 13, 2019
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.
Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.
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.
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.
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.
I think it would help if Data Science Studio added some more features and improved the data model.
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.
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.
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.