Looker
Tableau
Microsoft Power BI
Sisense
Domo
Qlik
QlikSense
Google Analytics
Boxes.dev
Codesphere
AppWizzy
InstaVM
Defang
Daytona
DigitalOcean
opencode
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.
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Based on our record, Looker should be more popular than Boxes.dev. 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.
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: over 3 years 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 / almost 4 years ago
We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / over 4 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 4 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 4 years ago
Devin Automations is the most obvious one: solid UX, but can get very expensive to run. There are also a bunch of newer startups in this space. I'm building one myself, https://boxes.dev -- we're very early but building for this exact use case. Some other ones worth a look are Factory Droid and Amp Orbs. Those two build their own agent harness (like Cursor), whereas with boxes.dev we run the native codex and... - Source: Hacker News / 2 days ago
These tools all assume you have machines to run the agents on. But for parallel agents I'm pretty convinced you want each agent on its own isolated devbox running your dev environment (not e.g. Worktrees on one box) - which isn't trivial to set up and manage. I'm working this with https://boxes.dev - a workspace for launching and managing claude + codex sessions, each running in its own cloud devbox. We launched... - Source: Hacker News / about 1 month ago
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.
Codesphere - Deploy in less than 5s
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
AppWizzy - Build scalable web apps and websites with AI that serve you for years. Professional vibe-coding platform. Perfect to build SaaS, intenal tool, AI tool, business app, etc
Sisense - The BI & Dashboard Software to handle multiple, large data sets.
InstaVM - Instant computers for AI agents