Dataiku vs. Pecan.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

Pecan is something that few know and that I feel can represent a great utility for an entire company, to focus and prioritize all its products and services in favor of the right path, avoiding making mistakes and jumping directly to the solution of future problems before they happen. Pecan will allow you to always be one step ahead and improve your trading system quickly.

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

• One of the main important characteristics is its ease of use and the intuitive nature of the platform. It is possible to carry out analyzes quickly and efficiently without requiring user experience. This positive point really gives us what we need for our work: optimization and automation.
• The creation of reports and statistics allows us to fully visualize the analysis carried out, in order to develop our work and carry out the pertinent actions.
• Segmentation allows us to prioritize potential customers, more focused marketing campaigns, highlight our services with what our public is really interested in.

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

I particularly believe that CrossEngage has some features that Pecan does not offer, such as A/B Testing, however, we were looking for a good predictor and analyst and the truth is that Pecan does its job very well.

Incentivized

• Customer satisfaction
• Timely project delivery

Incentivized