Databox vs. Dataiku

I believe Databox can be an asset for any company. We are a small company, but I can see the value for large companies too. Databox is a great fit for departments or organizations that need to put their data into a readable form without needing a ton of reports. Databox allows you to save time and put together a nice report without having to do too much extra work. Once it is set up, it basically runs on its own at the frequency you set. I personally receive a daily report and have it sent to the respective people on the day of our meeting so we can quickly review it.

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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.

Incentivized

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• Create dashboards from a variety of data sources.
• Set & track goals based on the data and metrics provided.
• Send alerts and scorecard updates to Slack and email automatically.

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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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• Some types of data can only be reported on for 1-2 months back. Unless I'm misunderstanding the function of the software this seems really weird. I can't figure out how to report on Activities more than 2 months ago

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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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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

Databox is an intuitive, well-designed platform that can be used by non-technical marketers. It is easy to learn, and while set up takes time, usability is high and the team has enjoyed creating custom dashboards and clients have also given us great feedback regarding its usability and value. While other BI tools are much more complex to navigate, Databox is a breeze.

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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

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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I have really enjoyed using Databox and have seen the value of it in many ways. They also continue to improve the functions of it and grow their integrations and templates. I look forward to continuing to use Databox in the future, potentially even finding ways to incorporate it into other departments to help them with reporting as well.

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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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Databox is unique in its ability to report from multiple data sources. Google Analytics is the standard when it comes to web metrics, but it's just one of the tools that integrates with Databox. Tableau is fantastic for data visualizations and reporting, but it's much more expensive than Databox, so it's not ideal for everyone. Tableau is also superior with customization

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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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• It has helped us to show our value to clients
• Easily digestible dashboards make it easy to understand what you're looking at

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Independently Invited by TrustRadius

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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