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Tableau offers templated visualizations. You generally do not need to program to create stuff. Observable is a notebook environment where you can write JS (most

Tableau offers templated visualizations. You generally do not need to program to create stuff. Observable is a notebook environment where you can write JS (mostly) to create and tweak highly customized visualizations. It's similar to Jupyter on a very high level (they all have reactive cells for example), but for JS and visualizations.

silentsea90 6y ago
That makes sense! Thank you! Some more questions: 1) Assuming the bulk of folks use jupyter notebooks for analysis, why not integrate with jupyter or use d3.js in jupyter directly? I assume there would be a learning curve for data manipulation on js where analysts/scientists would prefer python 2) Assuming that this isn't even meant for the jupyter audience, who is it meant for within a company?
- tracyhenry 6y ago
  I mean this is my question as well: how are they making money? As of right now Observable seems like a mix of use cases like Medium-like explanation articles, vis debugging/authoring and interactive journalism that don't seem to generate much money (ofc I can be wrong). I totally agree with you that the DS community is much much larger than the vis community. With the new funding round I think they should start doing something with DS.
  - carls 6y ago
    It looks like their current plan for monetization is a per user subscription fee for added features on the notebook: https://observablehq.com/teams https://observablehq.com/teams Given the marketing on the page, it also looks like it's targeted at business use cases (i.e. a bunch of data scientists who want to visualize something in d3 but also want to collaborate).
- carls 6y ago
  I definitely think it's a good point to support Python/R for data manipulation, and allow to also JavaScript for complex visualizations. Their current target for paid customers seems to be infoviz folks at news outlets (the CTO and co-founder was at NYTimes' data viz team for a number of years): https://observablehq.com/teams https://observablehq.com/teams That doesn't seem like a huge market, but perhaps they're starting with this audience segment and will be branching into more DS-type features (i.e. supporting a Python kernel, trying to be a more feature-rich Jupyter).

silentsea90 6y ago

That makes sense! Thank you! Some more questions: 1) Assuming the bulk of folks use jupyter notebooks for analysis, why not integrate with jupyter or use d3.js in jupyter directly? I assume there would be a learning curve for data manipulation on js where analysts/scientists would prefer python 2) Assuming that this isn't even meant for the jupyter audience, who is it meant for within a company?

tracyhenry 6y ago
I mean this is my question as well: how are they making money? As of right now Observable seems like a mix of use cases like Medium-like explanation articles, vis debugging/authoring and interactive journalism that don't seem to generate much money (ofc I can be wrong). I totally agree with you that the DS community is much much larger than the vis community. With the new funding round I think they should start doing something with DS.
- carls 6y ago
  It looks like their current plan for monetization is a per user subscription fee for added features on the notebook: https://observablehq.com/teams https://observablehq.com/teams Given the marketing on the page, it also looks like it's targeted at business use cases (i.e. a bunch of data scientists who want to visualize something in d3 but also want to collaborate).
carls 6y ago
I definitely think it's a good point to support Python/R for data manipulation, and allow to also JavaScript for complex visualizations. Their current target for paid customers seems to be infoviz folks at news outlets (the CTO and co-founder was at NYTimes' data viz team for a number of years): https://observablehq.com/teams https://observablehq.com/teams That doesn't seem like a huge market, but perhaps they're starting with this audience segment and will be branching into more DS-type features (i.e. supporting a Python kernel, trying to be a more feature-rich Jupyter).