Saturn Cloud
Amazon SageMaker
Deepnote
Apache Zeppelin
Databricks Unified Analytics Platform
Azure Synapse Analytics
GeoSpock
Google BigQuery
Looker
Tableau
Microsoft Power BI
Sisense
Domo
Qlik
QlikSense
Google BigQuery
Saturn Cloud is an award-winning ML platform with 75,000+ users, including NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. It is an all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Users can spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, build large language models, and more in a completely hosted environment.
Data scientists and analysts work best using the tools they want to use. You can use your preferred languages, IDEs, and machine-learning libraries in Saturn Cloud. We offer full Git integration, shared custom images, and secure credential storage, making scaling and building your team in the cloud easy. We support the entire machine learning lifecycle from experimentation to production with features like jobs and deployments. These features and built-in tools are easily shareable within teams, so time is saved and work is reproducible.
Looker is a business intelligence platform with an analytics-oriented application server that sits on top of relational data stores. The Looker platform includes an end-user interface for exploring data, a reusable development paradigm for creating data discovery experiences, and an extensible API set so the data can exist in other systems. Looker enables anyone to search and explore data, build dashboards and reports, and share everything easily and quickly.
Saturn Cloud LookerSmooth and bug free experience. There are ready data science images with pre loaded packages for most common scenarios, making you focus on the project/problem and leave the infrastructure part to Saturn Cloud.
True story, way better than just sweating Colab. The best and cheapest compute services there is.
I have started using this to run the computations which generally require like 64+GB of RAM, and the procedure to setup the enviroment is also nice. Got all the R packages running smoothly.
Based on our record, Looker should be more popular than Saturn Cloud. It has been mentiond 14 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Not 100% sure of your intention, but if you work with python, and you're familiar with (or can spend the time learning) dask, and willing to pay, you can consider coiled.io or saturncloud.io that offer managed dask that you can scale and use GPUs etc (again, not sure if applicable to your use case). Source: about 1 year ago
SaturnCloud - Data science cloud environment, that allows to run Jupyter notebooks and Dask clusters. 30 hours free computation and 3 hours of Dask per month. - Source: dev.to / over 1 year ago
I think your site looks good and I have used the type of service you offer, but there are 2 potential problems. As SheepherderPatient51 said,Google already offers all of this for free (and so does https://kaggle.com and https://www.paperspace.com ). There are also other sites just like yours such as https://deepnote.com,https://saturncloud.io, and https://lambdalabs.com . Source: over 1 year ago
* How does it differ from other GPU cloud providers that offer ready to use Jupyter notebooks? (E.g. https://support.genesiscloud.com/support/solutions/articles/47001170102-running-jupyter-notebook-or-jupyterlab-on-your-instance or https://saturncloud.io/). - Source: Hacker News / about 2 years ago
At the moment I am going to go to https://saturncloud.io/ or https://www.cloudeo.group/. Source: over 2 years ago
Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the folders if you have set the permissions correctly for each folder). Source: about 1 year ago
Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins that can make Kimball warehouses hard to navigate for business users. - Source: dev.to / over 1 year ago
We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / about 2 years ago
Dashboard: I like to use Datastudio because it's easy (just like using google sheets), but you can also try out Looker. Source: over 2 years ago
For Growth and larger, I would recommend Looker. The only reason I wouldn't recommend it for the smaller company stages is that the cost is much higher than alternatives such as Metabase. With Looker, you define your data model in LookML, which Looker then uses to provide a drag-and-drop interface for end-users that enables them to build their own visualizations without needing to write SQL. This lets your... - Source: dev.to / over 2 years ago
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Deepnote - A collaboration platform for data scientists
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Sisense - The BI & Dashboard Software to handle multiple, large data sets.
