Databox
Geckoboard
Klipfolio
Grow
Whatagraph
Google Data Studio
Looker
Google Chart Tools
Deepnote
Apache Zeppelin
Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Azure Synapse Analytics
Google BigQuery
GeoSpock
Databox is modern Business Intelligence software for teams that need answers now. It offers the best of BI, without the complicated setup, steep price, or long learning curve. It helps growing companies make their data more usable, by making it accessible to their entire team so they can make better decisions, faster.
It provides a blend of powerful, but easy-to-use features like:
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Databox
DeepnoteBased on our record, Deepnote should be more popular than Databox. It has been mentiond 34 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.
Databox โ Business Insights & Analytics by combining other analytics & BI platforms. Free Plan offers 3 users, dashboards & data sources. 11M historical data records. - Source: dev.to / over 2 years ago
You need a plan that gives you access to workflows, and the ad events tool. If you can also get the lower tier of a paid databox subscription for reporting. Source: over 3 years ago
I've actually just read about this service on another post, but if it's just a way to display the data from a Google Ads account that makes it easy to interpret and to share then you can get a free account here: https://databox.com. Source: over 3 years ago
Another option is to go with something like https://databox.com/ with built-in reporting. $250 just to white label the reports seems excessive though. Source: almost 4 years ago
Databox โ Business Insights & Analytics by combining other analytics & BI platforms. Free Plan offers 3 users, dashboards & data sources. 11M historical data records. - Source: dev.to / almost 5 years ago
Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know... - Source: Hacker News / about 2 years ago
- https://deepnote.com -- also extensive AI integration and realtime collaboration. - Source: Hacker News / about 2 years ago
Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors. - Source: dev.to / over 2 years ago
We looked into many of these issues with Deepnote (YC S19) [https://deepnote.com/]. What we found is that these are not necessarily problems of the underlying medium (a notebook), but more of the specific implementation (Jupyter). We've seen a lot of progress in the Jupyter ecosystem, but unfortunately almost none in the areas you mentioned. - Source: Hacker News / about 3 years ago
Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / over 3 years ago
Geckoboard - Get to know Geckoboard: Instant access to your most important metrics displayed on a real-time dashboard.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Klipfolio - Klipfolio is an online dashboard platform for building powerful real-time business dashboards for your team or your clients.
Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
Grow - Grow is a business intelligence software that empowers businesses to become data-driven and...
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.