Dataiku vs. InetSoft Style Intelligence

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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It's great for the accumulation and assimilation of various data formats to be channeled into a single end-point, whether that be a table or a report. It reminds me so much of SPLUNK in that regard. The application is also very easy to use and has been configured in such a way that it is appealing and productive for both novice and expert users. I was able to pick up the basis after a solitary day's training. We've mainly used it to create bespoke dashboards and visuals, thereby allowing for effective report writing. This was a major consideration from Senior Management before the application was purchased. There haven't been any real drawbacks with the software thus far.

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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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• Easy to use with a very user-friendly interface, making onboarding with the tool a lot easier.
• Able to mash up/integrate data from different sources and file types which helps a lot with consolidation.
• Good customer service/support that makes solving problems/issues a lot faster.

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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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• I think the user interface is in need of an upgrade, as its starting to show it's age a little. It looks like it needs a rehaul in the department.
• Hopefully, the company can grow and then have more frequent interactions with their customers.
• I am slightly wary that support may not have the same proficiency at the very highest level, as my company reaches the expert user level.

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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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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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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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InetSoft is a more cost-effective option that offers the same functionality, features, and usability. It is a great option, especially for SMEs. It also has top-notch customer service/support which is a key factor in selecting any agency or tool. I recommend using InetSoft especially for small businesses

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• Customer satisfaction
• Timely project delivery

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Independently Invited by TrustRadius

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• Reduction in excessive space for data storage repositories
• Faster time to analyse data and metadata. Quicker to reach objective analysis
• Conclusive informational reporting

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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