Cloudera Data Platform vs. Dataiku

I have seen that Cloudera Data Platform is well suited for large batch processes. It works really well for our indication analyses that are performed by the actuaries. I feel that rapid streaming operations may be a situation where additional technology would be needed to provide for a robust solution.

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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.

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• Scales
• Highly available

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• 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

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• Constantly changing costs
• Log visibility

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• 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.

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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

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We have utilized Cloudera support quite frequently and are very satisfied with the capability and responsiveness of that team. Often, the new features delivered with the platform give us an opportunity to mature the way we're doing things, and the support team have been valuable in developing those new patterns.

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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.

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IBM's offering of the Cloud Pak for Data has been a moving target and difficult to compare to Cloudera Data Platform. We have implemented our solution on Amazon Web Services, which appears to be supported by IBM at this point, but the migration would be very expensive for us to endeavor.

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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.

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• Reduced operational costs
• Speed to market

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• Customer satisfaction
• Timely project delivery

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info