Databox vs. Jupyter Notebook

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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I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.

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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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

• Simple and elegant code writing ability. Easier to understand the code that way.
• The ability to see the output after each step.
• The ability to use ton of library functions in Python.
• Easy-user friendly interface.

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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

• 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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• Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
• Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.

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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

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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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

Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.

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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

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.

Incentivized

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

I haven't had a need to contact support. However, all required help is out there in public forums.

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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

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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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

With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.

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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

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

Incentivized

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

• Positive impact: flexible implementation on any OS, for many common software languages
• Positive impact: straightforward duplication for adaptation of workflows for other projects
• Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration

Incentivized

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