Deepnote
DeepnoteReviews from AWS customer
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Great A/B testing took
What do you like best about the product?
It’s a great way to keep track of the A/B tests that we run. There are also great visualization tools for us to help craft a story for stakeholders.
What do you dislike about the product?
I wish there was a stat sig indicator that helps determine when we have reached significance and move forward with the winner of our tests.
What problems is the product solving and how is that benefiting you?
Helping us run redirect landing page split tests.
The Modern, Collaborative Notebook I Didn't Know I Needed!
What do you like best about the product?
The UI is hands down one of Deepnote's strongest selling points. It's incredibly clean, modern, and intuitive. Navigating through projects, organizing notebooks, and even just the act of coding feels so much smoother and more aesthetically pleasing than traditional Jupyter setups or other web-based alternatives. It genuinely makes the development process more enjoyable.
What do you dislike about the product?
Honestly, it's challenging to find significant downsides. If I had to nitpick, perhaps for users coming from very customized local Jupyter setups with many obscure extensions, there might be a slight learning curve or a feature or two they miss initially.
What problems is the product solving and how is that benefiting you?
Deepnote is solving several key problems for us:
Collaboration Bottlenecks: Previously, sharing notebooks meant sending files back and forth, dealing with version conflicts, and struggling to merge changes. Deepnote's real-time collaboration eliminates this entirely, allowing for seamless teamwork and faster iteration.
Environment & Dependency Hell: Setting up consistent Python environments across a team can be a nightmare. Deepnote handles this beautifully, ensuring everyone is on the same page with libraries and configurations.
Clunky & Outdated Interfaces: Many notebook tools feel dated. Deepnote provides a modern, enjoyable workspace that boosts productivity simply by being pleasant to use.
Accessibility & Sharing: Being cloud-based, it's easy to access our work from anywhere and share interactive notebooks or even apps with stakeholders who may not be technical.
Collaboration Bottlenecks: Previously, sharing notebooks meant sending files back and forth, dealing with version conflicts, and struggling to merge changes. Deepnote's real-time collaboration eliminates this entirely, allowing for seamless teamwork and faster iteration.
Environment & Dependency Hell: Setting up consistent Python environments across a team can be a nightmare. Deepnote handles this beautifully, ensuring everyone is on the same page with libraries and configurations.
Clunky & Outdated Interfaces: Many notebook tools feel dated. Deepnote provides a modern, enjoyable workspace that boosts productivity simply by being pleasant to use.
Accessibility & Sharing: Being cloud-based, it's easy to access our work from anywhere and share interactive notebooks or even apps with stakeholders who may not be technical.
Data science notebook that keeps improving
What do you like best about the product?
The continuous and frequent feature addtions. This has enabled me to keep improving my data workflows.
What do you dislike about the product?
Setting up virtual environments can be made easier.
What problems is the product solving and how is that benefiting you?
1. Ease to share notebooks with internal stakeholders to do simulations and analysis.
2. Prototyping data products.
2. Prototyping data products.
Really good for notebook style analysis
What do you like best about the product?
The ability to do custom analysis in python. AI code completion is a really good addition.
What do you dislike about the product?
Building apps in deep note is clunky. The out of the box data visualisations need more variety and flexibility. Its pretty limited at the moment
What problems is the product solving and how is that benefiting you?
Deepnote helps in doing custom notebook style analysis where you need a bigger compute power. So the ability to scale up and scale down machines has been really helpful in working with big data.
Simple to use, powerful and collaborative
What do you like best about the product?
I was looking for a notebook that can be easily shared, without the hassle of installing and configuring Jupyter or other tools, and Deepnote provides just that (and quite a lot more). It's easy to use, simple, powerful, and, importantly, makes teamwork coding easy.
What do you dislike about the product?
Some features, like exporting to Gsheet, could be made available in a more automated way (but I understand several new functionalities are currently being developed).
What problems is the product solving and how is that benefiting you?
Deepnote is making the sharing and collaborative work on python notebooks simple!
Deepnote Has Helped Me Raise my Data Science Game!
What do you like best about the product?
Flexibility and affordability. I have also found it to be more stable compared to Google Colab. Very rarely issues with disconnecting while training models
What do you dislike about the product?
I have found some functions easier to carry out in Colab such as integrating with Kaggle to automate data import
What problems is the product solving and how is that benefiting you?
Affordability and flexibility
Efficient ETL with Deepnote
What do you like best about the product?
Deepnote's AI assistant has been incredibly helpful in creating new code blocks and fixing issues, making it easier to manage the ETL process without prior extensive Python experience. The platform allows for smooth daily execution of the ETL process, which has been running reliably. The built-in secret management helps avoid hardcoding secrets directly into the code, providing a basic level of security.
What do you dislike about the product?
The interface can be slow to load, especially with a large number of code blocks. I wish I could get detailed information about past executions, both successful and failed, for troubleshooting and monitoring. The visibility of secrets in the secret manager poses a potential security risk.
What problems is the product solving and how is that benefiting you?
As a web-based platform, I can access my projects from anywhere without complex setups. The AI assistant helps me write and debug code, which is great since I don't have extensive experience with Python. I get immediate results, helping me quickly spot and fix issues in my ETL process.
Great and streamlined our processes
What do you like best about the product?
Sharing / no wall building between teams
What do you dislike about the product?
Integrations with data sources are limited with poor auth
What problems is the product solving and how is that benefiting you?
Allow sharing of work and analyses between teams and support junior members of the team learn how to code
It makes notebooks collaborative
What do you like best about the product?
Deepnote's search and ease of sharing. Prior to using Deepnote we had an awkward repo of hundreds of Jupyter notebooks. Finding specific notebooks was really hard. Sharing them even harder.
With Deepnote, search and sharing became really easy.
With Deepnote, search and sharing became really easy.
What do you dislike about the product?
I haven't yet intuited to the AI features and think that's a big opportunity going forward.
What problems is the product solving and how is that benefiting you?
Making our repo of Jupyter notebooks searchable and shareable. This became really important when we went from 1 DS -> 2.
Very useful and intuitive
What do you like best about the product?
The best part of using deepnote is to be able to combine different environments such as Python, SQL, files, etc. to be able to develop much faster. Also, the automation of tasks is very useful and allows you to keep track of errors very easily. I'm a hard user of Deepnote since I knew it. Also, the integrations are really useful and have everything I need.
What do you dislike about the product?
The AI functions are useful, but need to be improved. Sometimes I don't feel confident with this. Also, I would like to have more options to automate processes like ETL that are long-time-running projects but could be executed very easily with such a tool.
Also, plots could be limited and sometime I have to use python because plot feature is not enough.
Also, plots could be limited and sometime I have to use python because plot feature is not enough.
What problems is the product solving and how is that benefiting you?
Mainly connecting different data sources to be able to do transformations within SQL or Python. Likewise, also automating the updating of this data in other tools.
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