Deepnote
DeepnoteReviews from AWS customer
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Streamlined, Dedicated Environment Would Elevate Cross-Language Integration
What do you like best about the product?
Deepnote's ability to have multiple people working on a single document at the same time is a must-have for data science or analytics teams. It's like a Google Docs that came to Jupyter Notebook. This makes it easy to work across teams and streamline the workflow with little friction, despite daily use. Deepnote's AI integration also means that we can focus on just writing the code and leave it up to the AI to automate the syntax hygiene and documentation.
What do you dislike about the product?
The integration across different coding languages like queuring a data frame in SQL, then using it in R, or importing in custom or proprietary functions from a corporate GitHub is either missing, difficult to implement, or clunky. In these situations, it would be great to have it more streamlined and have a more dedicated environment running in the background to mimic the UI of other cloud services, like Posit.
What problems is the product solving and how is that benefiting you?
One of the biggest challenges in any data science or analytics team is the friction that comes up when working together on code and syntax. Too often, that friction leads to a handoff style of collaboration, where people pass progress back and forth instead of working in parallel. Deepnote helps enable more real-time collaboration through comments and live viewing of the work as it’s being done.
Reproducible experiments and analysis with Deepnote
What do you like best about the product?
Moving to Deepnote has transformed how we collaborate and share analysis, research, and experiments at PredictAP. The integrations allow us to connect to different data sources and easily run analysis with the help of AI-generated scripts. Notebooks are easily accessible, making experiments more reproducible without the overhead of setting up developer environments.
What do you dislike about the product?
The AI agent is helpful, but I still prefer using Claude Code directly. When prompting the AI agent in Deepnote, it creates many additional cells, which makes for a jarring experience—I often have to go back and clean them up. My workflow currently consists mainly of editing scripts in Claude Code and then copying them back into Deepnote. For data analysis, however, I do find the AI agent helpful for generating quick visualization scripts.
What problems is the product solving and how is that benefiting you?
Solving the ability to reproduce data analysis and experimentation - This helps us share and build on learnings throughout the team
Modern Python Coding with Seamless Integrations and Easy Collaboration
What do you like best about the product?
This is a very modern way to code in Python and integrate with other platforms and databases. It also makes it easy to work with others at the same time.
What do you dislike about the product?
If version control for the notebook were available, it would be perfect.
What problems is the product solving and how is that benefiting you?
I use Deepnote as the backend for my logic and automation.
Easy to Use, Notebook-Generated Documentation Shines
What do you like best about the product?
I like the ease of use and the “documentation” generated by the notebooks. I mainly consume dashboards created by the product team, but I can quickly verify how they arrived at the numbers and the conclusions they’re presenting.
What do you dislike about the product?
I would like to be able to interact with the code in a editor of my choice.
What problems is the product solving and how is that benefiting you?
It allows the creation of analysis over our data lake with easy, allowing anyone in our team to create a custom analysis with easy. Sharing and understand the analysis are also great.
Easy Access to Data, Smooth Experience
What do you like best about the product?
Easy access to datas. Work very well for my purposes.
What do you dislike about the product?
None. Deepnote is good for everything that i use for.
What problems is the product solving and how is that benefiting you?
Easy access to client data
Simple, User-Friendly Interface for Both Technical and Non-Technical Users
What do you like best about the product?
I like that it's very useable for both technical and non-technical users. The interface is simple to use and non-technical users can get exactly what they want on the front end.
What do you dislike about the product?
There's not much that I can complain about Deepnote right now. It has performed to my standards.
What problems is the product solving and how is that benefiting you?
I need to be able to see data and analyze data that is accessible for non-technical users. I need a quick dashboard, I need it to connect to a database so that I can generate dashboards and instantly understand the data through graphs.
Empowering Data Analytics Teams to Experiment and Build Data Apps
What do you like best about the product?
It’s helping improve the team’s capabilities in Data Analytics and enabling the Data team to experiment and build data apps.
What do you dislike about the product?
AI Assist is still quite limited. It would be much more useful if it included additional features that support building AI apps, or if it made it easier to integrate AI capabilities into more traditional data apps.
The dashboard and data visualization features also need improvement to provide a better end-user experience, especially in terms of usability and overall polish.
The dashboard and data visualization features also need improvement to provide a better end-user experience, especially in terms of usability and overall polish.
What problems is the product solving and how is that benefiting you?
Changing the data team culture and profile.
Sleek, User-Friendly UI Perfect for Lean Data Teams
What do you like best about the product?
Simplicity and user friendly UI - reason why I signed up.
What do you dislike about the product?
I was using for ETL pipeline to snowflake and supabase. Timing of workbook runs does not support a full production-ready solution. Not sure why we cannot use multiple run times.
UI is great, very simple. Using Prefect for ETL transformations now, no need for deepnote syncs. Otherwise, great product for lean startups and data sci teams.
UI is great, very simple. Using Prefect for ETL transformations now, no need for deepnote syncs. Otherwise, great product for lean startups and data sci teams.
What problems is the product solving and how is that benefiting you?
Simplicty and clean UI. Lambda AWS is disgusting - too many configs and too enterprise heavy.
Deepnote Elevates Our Data Science Workflow
What do you like best about the product?
We use Deepnote for data science at our company, and it’s been a great experience. It’s easy and intuitive to use, and the UX is clean and well-designed. I also really like the color scheme.
What do you dislike about the product?
Larger notebooks can occasionally be slow to process. Even so, it hasn't caused a significant problem for our daily operations.
What problems is the product solving and how is that benefiting you?
Deepnote is helping us process data in real time at a faster speed than any other platform we considered using.
Powerful Query Processing and Visualization in One Platform
What do you like best about the product?
The power in the query processing. It's great when doing heavy queries and data visualizations - all in one.
What do you dislike about the product?
You should create a feature on downloading .csv files or .xlsx each query or data results. That would be helpful to later export it to sheets.
What problems is the product solving and how is that benefiting you?
I appreciate having an all-in-one data analytics platform that allows me to create complex queries and connect them directly to my database. This integration makes it much easier to manage and analyze my data efficiently.
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