Dataiku vs. Zoho DataPrep

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

Scenarios where it works well: 1. Preparing reports like CRM, Marketing, and sales for monthly reports. 2. Cleaning CSV files with inconsistent format 3. Removing of duplicates and finding error values 4. Enabling non-technical people to manage data preparation without coding. Scenarios where it is less appropriate: 1. Processing real time data and large scale data needs 2. Deep customization at code level 3. At advanced predictive modeling

Incentivized

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

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

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

I would rate Zoho DataPrep a 10/10 for its usability because I feel it is very easy and intuitive platform and even non-technical people can access it easily without coding knowledge. Also, its workflow builder is very straightforward, once we create any data pipeline then we can reuse it easily.

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

Zoho DataPrep is much easier to use and quick to set up. It user interface is very user friendly, even people with no technical knowledge can use it easily to transform the data. It creates the repeatable workflows easily and more cost-effective for small to mid-size teams. We selected it because it aligns with our business needs and goals perfectly like fast, easy, and efficient for everyday use.

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