Cloud providers offer so many products with so many nuances that I'd posit it's practically impossible to do a satisfying pricing comparison that's even halfway comprehensive. That's not the fault of the author, certainly, but the title makes it come off as something far more comprehensive than it actually is, and as a result comes across as disingenuous.
Amazon’s policy is even better than that (IMO). They know that no one reads things before meetings, so it’s accepted that everyone will quietly read for the first part of the meeting (as much as half the total meeting duration). Then (and only then) when everyone has finished reading the same material does anyone speak up to ask questions or share input. Saves a lot of time in meetings, although it adds a lot of time in preparing documents. I suspect it probably nets out to positive time savings and am confident it results in more informed decision-making.
This isn’t the complete picture. It’s true that the vesting schedule gives you only 5% of RSUs in your first year, but employees’ cash signing bonus is increased to offset that. So if the total compensation target for a role is generally $500k (say, a principal engineer or a director, maybe?) and your salary is capped at $160k, you’d be given a signing bonus of $500k-$160k-(total stock vest x 5%) in cash. It’s not as though you’re paid significantly less when you start, it’s just that how you are paid is different.
The point is summarized well by one of my favorite aphorisms (often attributed incorrectly to Mark Twain): "I have never let my schooling interfere with my education."
You can always do both. That’s what I’m doing, and it has served me well so far (just graduated from MBA with solid job placement and I have a few courses to go for OMSCS).
> a wise businessperson would see this as a signal that their product offering doesn't actually match demand, and work to fill that demand
This is not necessarily true. It depends entirely on the shape of demand. By way of simplified example, imagine that there are two types of consumers equally distributed: those willing to pay $1000 and those willing to pay $100. Unless you can distinguish at time of payment between these users and charge them different prices (without possibility of resale), you will always be better off forgoing half of the market and charging only the higher price.
It's possible that the business has estimated things incorrectly and is acting suboptimally, but I think it's as least as likely that they are maximizing profits the way we'd expect a rational business operator to do.
Only if it's a very competitive market, and even that effect will only happen over time.
Product differentiation introduces pricing power for individual firms, and depending on the style of competition you think will occur (e.g., Cournot oligopoly vs. Bertrand), you may very well never approach anything close to perfect competition with the small number of firms there are in this market.
Reminds me of a similar article that measured a similar kind of question about the wait times for NYC subways conditional on how long you've been waiting (https://erikbern.com/2016/04/04/nyc-subway-math.html). I think it's a pretty safe bet that people who like this post will like this article as well.
I can understand the rationale for why Amazon would build something like this. Amazon owns a large chunk of the market of ecommerce in instances when customers already know roughly what they’re looking for. A big growth opportunity that’s mostly untapped for them is convincing people to do their serendipitous, casual browsing (think: walking through a mall and seeing what’s on display) on Amazon. This is their latest attempt to capture that use case and foster that kind of “daily habit” type mentality (see also their gold box deals and similar product features).
One thing that’s unclear to me is why they’d use Instagram as their inspiration rather than Pinterest when the latter more clearly lends itself to shopping, and when there’s a natural tie-in with Amazon’s wish lists functionality (totally conceivable to change wish lists into some kind of Amazon pinboards).
I completely agree. Almost all of this article appears to have little to do with being a Data Scientist in particular and more to do with some good practices for writing code in general. So the advice itself is fine, just not what I was hoping for based on the title.
Reproducibility, like you say, however, is something that is an issue far more particular to data science, and worth more serious consideration and discussion. Hand-in-hand with that is shareability. I'm a fan of what airbnb has open sourced to address some of those issues in their knowledge repo project: https://github.com/airbnb/knowledge-repo
Cloud providers offer so many products with so many nuances that I'd posit it's practically impossible to do a satisfying pricing comparison that's even halfway comprehensive. That's not the fault of the author, certainly, but the title makes it come off as something far more comprehensive than it actually is, and as a result comes across as disingenuous.