Comment by nzoschke
11 hours ago
This looks great.
"Unbundling BI" is absolutely where things are headed now that more people have agents, coding agents, agent computers to help with work.
I'm seeing this all up and down knowledge work tools. I've started treating email as a BI problem -- ETL it from Gmail and and create many different views into it and reports from it.
I just wrote up some thoughts on that here: https://housecat.com/blog/making-gmail-data-fast-for-humans-...
A natural followup is how to better visualize this data in chat. The DBT table component looks like it could help https://docs.dbtcharts.com/charts/tables/
Wow https://github.com/dbt-labs/dbt-charts has a great chat user / agent coding experience:
> Make charts of this with dbt Charts. Start with: uv tool install dbt-charts && dct skills intro
>> build a dashboard of my hiring inboxes: list of candidate name / email / locale, application quality, response age
The one-shot dashboard is surprisingly good.
>This looks great.
>"Unbundling BI" is absolutely where things are headed now that more people have agents, coding agents, agent computers to help with work.
Agreed. Coupled with bento[0] for slide decks, I think this type of project is a very welcome development, helping us move away from walled gardens and proprietary software suites.
[0] https://github.com/nyblnet/bento
Thanks for sharing this too. It reminds me of GistDeck a super old project that turned a gist into slides. Infinitely better than powerpoint or GSlides.
https://github.com/nzoschke/gistdeck
Why visualize data? Graphs and charts always felt like the "show your work" in math class. It is forced synesthesia.
The rocket either lands or doesn't, safely, as expected. Green and Red lights are abstracted data plots.
The context should be the focus.
"Rocket must land at less than 0.2/mps" and pump the data into that context filter, more - reduce velocity, less - green light.
> Why visualize data?
Because your eyes are enormous bandwidth channels hooked right up to your brain. So high that we can take things like writing which is just a small part of your fov and a set of squiggles that roughly corresponds to sounds you’ve heard and effortlessly comprehend it.
> The rocket either lands or doesn't, safely, as expected.
Crash vs land is a terrible amount of data to have if you want to fix it for next time. Did it accelerate suddenly? Is there a lurch? Did all the accelerometers have a small jump at the same time? Visualising data in different ways can really help show patterns.
Not every visualized data point is tied to a binary decision.
e.g. when highlighting a quarterly revenue result, there is a big difference between missing the target by 1% or 50% (and of course the absolute number behind it is also important).
And on a larger scale, trajectory is also something that is easily visualized in graphs, and hard to boil down to a binary marker.
There certainly is a lot of "forced synesthesia", and more looking at charts than necessary out there, especially when decisions are then made more from the gut than based on the data one is claiming to base the decisions off, but a culture of binary-based decision making is just as bad of an idea.
I've worked in data for 15 years and I've never heard this argument. I love it :)!
Who knows, with AI this may be the future. Visualizations were created to help us understand data. Florence Nightingale published them "to affect thro' the Eyes what we fail to convey to the public through their word-proof ears."
Often a formula better represents a situation. But I'm not sure how much impact they'd have in spreading that understanding outside of a formula-minded audience.
I worked deep in big data briefly. Billions is too big for humans so we got creative how we visualized and filtered.
AI slop has a "smell" meaning there's an abstracted data filter that results in rose or poop output. Shakespeare variable says the name doesn't matter.
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Sure, machines don't need visualization (although it seems that images are a surprisingly good medium to get context into agents), but humans still do. Mathematicians have plotted functions for a long time now. While the pure truth lies in the definition of f(x), the visualization helps the mind to grasp what it actually is. Humans will run companies for the foreseeable future, and so we will need visualization for the foreseeable future
Humans steer the ship. The wind and sea do the work. How we harness is what is changing.
Actually I think they do. Visualizations are a form of compression and focus.
All of my ai-driven plans use a tool I built to rasterize all text based visualizations. And I make the model present the rendered version to a clean room agent for brief-back. They go in circles until the diagram is good. Then, I instruct planning tools to always look at both the text and rendered version of all diagrams. I have found it to be surprisingly powerful.
Without guidance my agents tend to make me read CSVs.
Sure the data is correct, but it's obviously way easier for me to read it as a properly rendered table. Then you want to sort, group, aggregate the data. Visualize it many different ways if you will :)
Table and check marks in Markdown.
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