Dataiku vs. Plotly Dash

Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.

Incentivized

Plotly Dash suits well where you need to build a web-based reporting tool as a minimum viable product. You will be surprised when you build your first hosted web-based reporting tool in a few minutes without the need for web development expertise. However, when it comes to building a more complete solution, you may feel a bit restricted by the options provided by the API. But as you imagine, this is the cost of the abstraction of the web development layer, in other words, simplicity vs completeness. Still, Plotly Dash is a powerful option whenever you prefer simplicity over completeness.

Incentivized

• Low-code platform.
• Open source version includes most valuable modules.
• User friendly documentation.

Incentivized

• Simple codes to create quick graphs.
• Nice exportable figures.
• Good for the initial exploratory analysis of the data.

Incentivized

• The visualization feature of flow still has a lot room to improve, when the flow is complex.
• The "non-coding" template/building block for deep learning lack of many important configurable parameters.
• Lack of the unified way to allow applying the "design pattern" on the Python codes (if we want to develop our own module or building blocks.

Incentivized

• React JSX syntax support can be added/improved.
• Built-in UI components can be improved.
• The API used for AJAX calls can be made more understandable and simpler.

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 amazing part of Dataiku DSS is their customer service. Based on urgency and technical level, you get a reply from the Dataiku engineer when you raise a query. So far, my queries have been pretty complex to solve, so I have received solutions even from the CTO of the company as well, which is why I would describe their customer support as very good.

Incentivized

Dataiku was selected for me, but I am happy about that. I like Dataiku for the user experience, it feels less code-y and I like to demo things to non technical stakeholders because they can still follow along. When you open some other notebooks, you can see that peoples eyes start to glaze over

Incentivized

Incentivized

• So far it has had a positive impact. Multiple departments are coming to us with their business problems.
• I can't specifically say about ROI as I'm a developer, though I have heard this solution is economical compared to other AI/ML enterprise tools.
• By using this tool, my client has let go of software that was used earlier, and we have created a simpler framework to replace that software.

Incentivized

• Reduce product monetization lead time
• Real time performance monitoring
• Deep learning to allow better marketing segmentation models

Incentivized