11–20 of 22 posts
meh... for me number 1 should be: do they understand domain knowledge beats fancy analytics hands down most of the times or do they spend their time optimizing things nobody cares about?
Also - the best tools money can buy? Where does money come into data science tools? Tensorflow = free, RStudio = free, Shiny = free (ok you can get commercial versions of the last two, and we have, but they are cheap!) Sparklr = free, Python = free....
The original Joel Test was a piece of content marketing by Joel Splosky, the CEO of the company that builds FogBugz among other tools for collaboration among software engineers. This appears to be the same. We should evaluate it its merits: Are these useful questions to ask in pursuit of a more productive and less frustrated data science team?
A thinly veiled sales pitch for a "data science collaboration platform" is trotted out as some profound measure of how attractive a given company is to prospective applicants for data science positions. I'm wary of the Joel Test and others like it for one very simple reason: the points are goals to strive towards, not some filter by which prospective employers should be judged. Especially in the case of a fledgeling…
The original Joel Test was a piece of content marketing by Joel Splosky, the CEO of the company that builds FogBugz among other tools for collaboration among software engineers. This appears to be the same. We should evaluate it its merits: Are these useful questions to ask in pursuit of a more productive and less frustrated data science team?
Another that may not apply is the stuff about reproducing past experiments. Suppose your experment platform is programmatic and interfaces with some codebase. Old feature flags are a form of tech debt that should be removed. So old experiment code is sitting in a repo history somewhere but not necessarily deployable.
Ok - "latest tools without IT"; let's imagine that you have valuable or personal data, someone picks up an unchecked tool and heyyyyy presto! You lose all that data (well, you still have it, also other people have and your company is in the newspapers). Also - the best tools money can buy? Where does money come into data science tools? Tensorflow = free, RStudio = free, Shiny = free (ok you can get commercial version…
Even open source options can require expensive eng/ops resources to set up a cluster.
The original Joel Test was a piece of content marketing by Joel Splosky, the CEO of the company that builds FogBugz among other tools for collaboration among software engineers. This appears to be the same. We should evaluate it its merits: Are these useful questions to ask in pursuit of a more productive and less frustrated data science team?
I don't see the need to make the Joel Test sound so nefarious. The Joel Test was content marketing, yes, but not of the FogBugz tool (while a bug database is item 4 out of 12, he doesn't even plug FogBugz in the item - it was a recruitment piece more than a sales piece). The reason we're still talking about the test is that it really struck a chord - it listed practices that were true and important, but not widely he…
Don't even think about Hall testing. And the people that hired me asked no question about my coding ability nor my Github account. And it is not a small company, nor an isolated thing.
And don't ask about the tooling, i spend my days fighting it... not being able to use package manager due to bad proxy is a PITA.
The Joel Test is still on my list of things to check with every company that want to hire me now. Because i see what happen when it is not respected every day...
The original Joel Test was a piece of content marketing by Joel Splosky, the CEO of the company that builds FogBugz among other tools for collaboration among software engineers. This appears to be the same. We should evaluate it its merits: Are these useful questions to ask in pursuit of a more productive and less frustrated data science team?
I don't see the need to make the Joel Test sound so nefarious. The Joel Test was content marketing, yes, but not of the FogBugz tool (while a bug database is item 4 out of 12, he doesn't even plug FogBugz in the item - it was a recruitment piece more than a sales piece). The reason we're still talking about the test is that it really struck a chord - it listed practices that were true and important, but not widely he…
I actually love well-written content marketing as it is often highly educational. Other examples include:
- DigitalOcean paying people to write tutorials on server configuration
- MIT paying students to write blog posts on life at MIT
- Ksplice writing a post on the uses of strace.
meh... for me number 1 should be: do they understand domain knowledge beats fancy analytics hands down most of the times or do they spend their time optimizing things nobody cares about?
Ok - "latest tools without IT"; let's imagine that you have valuable or personal data, someone picks up an unchecked tool and heyyyyy presto! You lose all that data (well, you still have it, also other people have and your company is in the newspapers). Also - the best tools money can buy? Where does money come into data science tools? Tensorflow = free, RStudio = free, Shiny = free (ok you can get commercial version…
Well, the best analytics database for your use case may not be cheap. E.g. a column store database. Even open source options can require expensive eng/ops resources to set up a cluster.