Deepnote
DeepnoteReviews from AWS customer
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Simplifies our process and let's us collaborate in real-time
What do you like best about the product?
Easy, intuitive and very convenient to use. Our company's analytic process needs real time collaboration between our engineers, so it's really helpful.
Highly recommend this platform
Highly recommend this platform
What do you dislike about the product?
Speed with bigger data sets could be better. We would like data visualization to be more customizable.
What problems is the product solving and how is that benefiting you?
Team collaboration is really helpful.
Makes complex programming simple for large teams
What do you like best about the product?
I love that my team doesn't need to be a python expert in order to take advantage of the benefits of programming efficiencies and insights. My data science team does all of the magic of building the tools, and Deepnote allows my analysts to just point and click to get the insights they need. Could not be easier to use.
What do you dislike about the product?
You do need to understand how to use python and variables in order to get Deepnote setup, but for most programmers the learning curve is small.
What problems is the product solving and how is that benefiting you?
Deepnote helps us run our client's data against machine learning models to gleen insights that would normally take hours to find. It helps non-python experts be able to become more efficient in their roles and empowers them to come up with new ideas for data analysis.
That data analysis of ours is top-notch
What do you like best about the product?
Our data mining and analytics process is made easier because integration with PostgreSQL and Google BigQuery is ultra simple. No complicated configurations are required thanks to their simple integrations. We’ve been able to use Deepnote to build notebooks where we import all the data directly from Google BigQuery, make interactive visualizations and import the data. My team was able to review the data and provided me with immediate feedback after sharing the notebook with them.
What do you dislike about the product?
It has come to my attention that performance could drop when dealing with really huge data sets, which impacts the agility of analysis.
What problems is the product solving and how is that benefiting you?
To facilitate better teamwork in data analysis projects, we implemented Deepnote. In the event that we needed to find trends in consumer behaviour by analysing large amounts of data. We can run complicated analyses, see the results in real time and link directly to our database through Deepnote. Faster decision making and more complete project completion was possible thanks to the links that can be shared, which allowed us to immediately share our results with all parties involved.
Great product, easy to use
What do you like best about the product?
Integrates well with existing data warehouses and easy transition between pulling data from SQL and doing analysis on python/pandas
What do you dislike about the product?
The notebooks don't remember which data warehouse the sql code comes from every time I create a new cell. Also doesn't remember the last cell's language (sql, python).
What problems is the product solving and how is that benefiting you?
Deepnote makes it easy for me to keep track of my existing queries and analytics studies. Rather than having to create a document of copy-pasted images and tables I can do it all in one deepnote notebook.
Deepnote for digital pathology
What do you like best about the product?
- Running multiple notebooks simultanously
- Cool integration of github
-I appreciate the seamless file integration system and the efficient S3 integration.
- Cool integration of github
-I appreciate the seamless file integration system and the efficient S3 integration.
What do you dislike about the product?
• There aren’t enough AI environments; it would be great to have Torch, RAPIDS, and PyTorch Lightning environments.
• The terminal should be more than just an add-on—running code for training models would be much more convenient.
• An intermediate GPU between the V100 and the K80 could be useful, especially because the Nvidia driver on the K80 doesn’t allow running the latest models.
• The terminal should be more than just an add-on—running code for training models would be much more convenient.
• An intermediate GPU between the V100 and the K80 could be useful, especially because the Nvidia driver on the K80 doesn’t allow running the latest models.
What problems is the product solving and how is that benefiting you?
- Quick development on GPU
Excellent Product
What do you like best about the product?
Its easy to use and navigate, I like how the interface is designed.
What do you dislike about the product?
There is a learning curve and not too many instructions, you need to spend a lot of time to learn.
What problems is the product solving and how is that benefiting you?
It solved my complex analytical question for statistical analysis.
Excellent cloud notebook environment for analytics and data science
What do you like best about the product?
It's very easy to get started with Deepnote, and the environment is very comfortable if you like notebooks. In many ways it reminds me of JupyterLab but with a modern and enterprise feel. You can have multiple notebooks per project (something competitors don't allow) and it is extremely easy to deploy a dashboard or report with a few clicks.
The AI features are very handy and speed up the low value work of typing syntax correctly.
The AI features are very handy and speed up the low value work of typing syntax correctly.
What do you dislike about the product?
Data apps could be improved somewhat. It's hard to pinpoint but there are some improvements to be made on the responsiveness of the apps and the overall look.
What problems is the product solving and how is that benefiting you?
I need to have a single platform to hold and share my analyses. In addition it needs to have my data connectors and a good system for organization and sharing. Deepnote checks all these boxes.
Data manipulation - ETL - Database visualization
What do you like best about the product?
I like how easy are the integrations with databases and storage sources like s3 and github. we frecuently use it for data collection. so start a new project is very easy. it has some libraries alredy installed and the guidance makes the support very smooth. because is based on jupyter notebook, implementation of projects are the same we used to do it before
What do you dislike about the product?
Creating input controls, the buttons controls are complicated to use or program
What problems is the product solving and how is that benefiting you?
ETL environment, database access.
Helpful with AI feature otherwise just use CoLab
What do you like best about the product?
Workspace is convenient and user friendly
What do you dislike about the product?
They require you to pay to access the AI features (so CoLab is better if you want something free)
What problems is the product solving and how is that benefiting you?
It makes it easier to collaborate on multiple notebooks
Very good to integrate quick scrips to run on a schedule
What do you like best about the product?
How easy it is to set everything up and get your scripts to run on a schedule
What do you dislike about the product?
I would like to have more freedom to decorate and edit the appearance of the graphs that get reproduced
What problems is the product solving and how is that benefiting you?
The easy processing of setting up new simple scripts without having the trouble of setting up whole server to get cron jobs to run
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