Dataiku vs. National Instruments Vision Builder AI

Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.

Incentivized

The perfect scenario is a production environment where items are passing in front of a camera on some type of conveyor system. Vision Builder AI can be set up to inspect those items and make decisions that can be handled down the line (rejection, sorting, etc.). It's great if you have an isolated vision system as part of a larger system that needs to just pass on results. It's not as well suited if you need that code tightly coupled with other code, such as vision-guided robotics.

Incentivized

• Allows users to collaborate and monitor individual tasks
• Caters to both types of analysts, coders and non-coders, alike
• Integrate graphs and plots with visualization tools such as Tableau

Incentivized

• The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
• When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
• Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.

Incentivized

The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level

Incentivized

The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.

Incentivized

Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.

Incentivized

It all comes down to tradeoffs. Do you want something that is extremely flexible and full-featured or do you want something that is easy and fast to use? Sure there are things that you can't do in Vision Builder AI that you can implement in LabVIEW, however, the vast majority of the applications that we work on do not need that extra functionality so Vision Builder AI is the best choice for us. If we find out along the way that Vision Builder AI is not going to work for us at least we have all of the steps and parameters figured out that we can use when moving to LabVIEW.

Incentivized

• Customer satisfaction
• Timely project delivery

Incentivized