Count is a new type of data analytics application, where everything is based around notebooks.
Notebooks contain all of your analytics queries, alongside rich text, images, videos, and interactive controls. A notebook can be a simple static document, a fully interactive application, or anything in-between. They are backed up as you write, use state-of-the-art rendering technology to take full advantage of your machine, and scale down to stay readable on mobile.
Count connects to your data warehouse to run queries, so the data you see is always up-to-date. It also (optionally) intelligently caches results to minimise the load on your databases.
Based on our record, Blazer should be more popular than Count.co. It has been mentiond 11 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.
We use Pyodide at https://count.co and think it's pretty amazing! Congrats on the new release. I read about the snapshot support for Cloudflare workers and assumed it was a feature that Cloudflare had developed - the fact it may be coming to all users of Pyodide is great news. - Source: Hacker News / 20 days ago
Hi Reddit, after lurking here a while I've finally got something interesting to share - a new feature I've been working on at Count (https://count.co), which I wrote a blog post on here:. Source: 7 months ago
Hi HN, after seeing a lot of data engineering discussion here I thought it would be interesting to share a new feature I've been working on at Count (https://count.co). We've made possible to import and execute dbt models, compiling them on the fly with a custom compiler, and view results alongside other collaborators in real time. We built this because we heard feedback from our customers that debugging and... - Source: Hacker News / 7 months ago
Count | Senior Software Engineer | REMOTE within UK/Europe | Full-time | https://count.co Count is like Jupyter, Tableau and Miro combined in one tool. Data teams at some of the world's leading scale-ups use it for everything from iterating data models to performing deep dive analyses and telling impactful stories backed by data. We're a small team of 8, and we're looking for experienced software engineers who are... - Source: Hacker News / 8 months ago
Full disclosure: I do work for count.co, the canvas in which the guide was built. Source: 12 months ago
I try to avoid these tools wherever possible, given the choice I'd always go for tools like Blazer. https://github.com/ankane/blazer No such luck in my current role, Looker and PowerBI are both in use by different bits of the org and nobody has the ability to delve into the underlying figures. - Source: Hacker News / 4 months ago
As u/jaxn said you could use Blazer for this kind of thing. I would also look into materialized views or custom tables and a scheduled job that calculates the metrics they care about. That will take you a long way. Eventually you can use something like Metabase but I would put that off for as long as possible as it's really expensive and pretty involved. Source: 12 months ago
And it's Open Source: https://github.com/evidence-dev/evidence if you are into the Ruby on Rails world. It's super solid, and it's been an indispensable tool integrated to all my projects. - Source: Hacker News / about 1 year ago
I use Ahoy too, but I don't have very good visibility into the data. I should spend more time building queries and creating charts. I should probably set up blazer as well: https://github.com/ankane/blazer. - Source: Hacker News / almost 2 years ago
The Blazer gem provides a nice way to analyze the results easily. It is simple to install and allows SQL queries to run against tables. The query here shows that the candidate implementation is significantly faster than the original. - Source: dev.to / about 2 years ago
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