A counterpoint, from someone who’s worked on SaaS billing /MRR reporting for 10+ years - it’s usually more complicated than just exposing an API endpoint for precalculated MRR by month. Most analysis requires drilling into dimensions of MRR growth - by cohort, by billing period, etc - and so while Stripe exposing an API for MRR could be helpful, it won’t cover most of the cases for proper financial analysis for a SaaS business. There’s also the complication of how MRR is computed across companies and domains - it’s not a GAAP metric and no standardized definitions.
Hey, we do cool stuff with gbq billing, which helps reduce computing costs.
Basically, we show how much money every pipeline costs coming in BQ, executed in BG, or leaving it. We do not query your data (do not need permission to read or edit). Everything is done using GBQ logs. I mean, we do not use your information_schema either. What we saw from our clients is at least 10% compute cost reduction in 10-30 days after deployment. Happy to give a fee trial to test it out.
> Allred tweeted that the school achieved a 100 percent job-placement rate in one of its cohorts, and later acknowledged in a private message that the sample size was just one student.
When confronted about this on Hacker News, Austen defended himself with:
> I did say the hiring rate of a cohort of one student was 100%. And in the same tweet I said, in all caps BUT VERY SMALL SAMPLE SIZE. Odd how that doesn’t make the article, don’t you think?
Aha that’s a gem, it’s like that crypto company listed “audited by <some famous reliable auditor >”. They do not mention they failed the audit, but they “did” get audited.
Or Tether. "We realize - but hope you don't - that 'financial attestations' do not remotely resemble 'audits', but we're going to call this financial attestation an audit". And "If you don't fall for the first, we're going to tell you that we have had audits done but we won't release them because they're in Mandarin Chinese."
"For a few months in 2013, Allred camped out of his car while in Silicon Valley, and frequently describes this period as having been homeless. However, a deleted post on his blog titled 'Voluntarily Homeless in Silicon Valley' explains that he lived out of a car by choice."
I have a friend who is adamant that he lives out of his truck by choice, but it's hard to call it a choice when there's only one option. I wouldn't hold his feet to the fire if he later admitted he was in a rough spot (our friend group is all very clear on this situation). I had put Allred entirely out of my mind for a while, but I seem to recall his "homelessness" was characterized more by image than by practicality. Since we're being technical, it seems worth making the distinction.
I had this same debate here a few months ago, about people living out of their truck/van in Seattle, and the "choice" of it. There was more than one person that could (or would) not see the distinction. "I've seen plenty of social media and YT videos talking about how much they enjoy the experience".
Uhh, when people talk of living out of a vehicle in the context of homelessness, they're talking about people parked in the back corner of a Walmart lot with their laundry and many earthly possessions beside them, not social media creators making YouTube videos for "#vanlife".
“ Six of the eight authors were born outside the United States; the other two are children of two green-card-carrying Germans who were temporarily in California and a first-generation American whose family had fled persecution, respectively.”
The more interesting thing to me is that only one of them went to an elite American undergrad (Duke). Rest went to undergrads in India, Ukraine, Germany, Canada (UToronto has a 43% acceptance rate).
Why would that be of note, especially in America? I think it would be an interesting observation in China or Japan, or some other country which is generally less welcoming to immigrants than the US
First generation immigrants are still a tiny minority of the population. The fact that the entire team consists effectively of first generation immigrants says something, probably both about higher education and American culture.
One thing is that getting a PhD is a good way to get into the U.S. As a foreigner, many visa and job opportunities open up to you with the PhD.
For an American, it's less of a good deal. Once you have the PhD, you make somewhat more money, but you're trading that for 6 years of hard work and very low pay. The numbers aren't favorable -- you have to love the topic for it to make any sense.
As a result, U.S. PhD programs are heavily foreign born.
I think you have completely the wrong takeaway here...
The US population is around 330 million. The world population is 8.1 billion people. What is that 4%? If you took a random sampling of people around the world, none of them would be Americans. You're going to need a lot more samples to find a trend.
Yet when you turn around and look at success stories, a huge portion of this is going to occur in the US for multiple reasons, especially for the ability to attract intelligence from other parts of the globe and make it wealthy here.
I understand, but reality has to factor in — to get representative you would have to narrow your sample to English-speaking, narrow it to legal for long-term employment in the US, narrow it to having received at least an American-level higher education…
Isn't some of it have to do with it being a self selecting sample? If you come to America to study, you were a good student in your resident country leading to more chances of success than the average local citizen. Their children might be smarter on average.
Alternatively if you are coming fleeing persecutions you are enterprising enough to set up something for your children. That hard work inculcates a sort of work ethic in such children which in turn sets them up for success.
Speaking from experience as an immigrant myself.
I think all those are true, but if so the percentages of first-generation immigrants should increase as you ascend the educational pyramid. I believe it does from
undergrad to Phd, but not from general population to higher education, so clearly there are at least two very different worlds.
There is a motivation that comes with both trying to make it and being cognizant of the relative opportunity that is absent in the second-generation and beyond.
There are also many advantages given to students outside the majority. When those advantages land not on the disadvantaged but on the advantaged-but-foreign, are they accomplishing their objectives? How bad would higher education have been in Europe? What is the objective, actually?
It looks like you are roughly right, but still, a sampling of 8 students from this population is not likely to come up that way (by my calculation 1.4x10^-7)
Its really not; hiring within a single firm, especially for related functions, will tend fo have correlated biases, rather than being a random sample from even the pool of qualified applicants, much less the broader population.
Because there are plenty of people in the US who are neither immigrants nor the children of immigrants. In fact, they're probably a significant majority. So to have 8 out of 8 be members of the smaller set is rather unlikely.
Not when you consider that those people were pulled from a worldwide talent pool for a relatively niche topic. If you can recruit anyone you want in the world and end up with 8/8 Americans, that would be weird.
Not sure if we can claim this any more, what with texas shipping busloads of immigrants to NY and the mayor declaring it a citywide emergency, and both major parties rushing to get a border wall built.
The phrasing was "welcoming to immigrants", not "welcoming to the ever shrinking definition of good immigrants established by a bunch of octogenarian plutocrats".
"Illegal" is a concept - it's not conflating to assume that it's not the bedrock of the way people think.
Illegal immigrant is pretty well defined, an immigrant that didn't come through the legal means. The people hired by Google are probably not illegal immigrants.
Illegal is a status more than it is a concept. Immigrating illegally is not the central definition of immigration, any more than shoplifting is the central definition of customer.
America is much more welcoming of immigration, by which I mean legal immigration, than Japan or China. This is not in dispute.
It is also, in practice, quite a bit more slack about illegal immigration than either of those countries. Although I hope that changes.
>America is much more welcoming of immigration, by which I mean legal immigration, than Japan or China. This is not in dispute.
It's not? It sounds like you know little about the world outside of America. Japan is stupidly easy to immigrate to: just get a job offer here at a place that sponsors your visa and it's pretty trivial to immigrate. Even better, if you have enough points, you can apply for permanent residence after 1 or 3 years, and the cost is trivial. In America, getting a Green Card is very difficult and costly, and depending on your national origin can be almost impossible. In Japan, there's no limits at all, per year or per country of origin, for work visas or PR. Of course, Japan is somewhat selective about who it wants to immigrate, but America is no different there, which is why there's such a huge debate about illegal immigration (in America it's not that hard; in an island country it's not so easy).
Yes, this is one of the actually admirable qualities of the US and California in particular. CA has one of the world’s largest economies because it attracts and embraces people from just about every part of the world.
I love that this is trending on HN. LLMs be damned. We still have lots of “simple” problems to be solved, like how to effectively write and share an ERD.
A LLM would probably make this better. Instead of asking the user to learn a DSL why not just translate SQL to whatever structure the render functions uses?
> In our experience, the BI layer is the weakest part of the modern data stack. The BI layer has a poor developer experience, and decision makers don’t really like the outputs they get. It turns out, these two issues are closely related. The drag and drop experience is so slow and low-leverage that the only way to get all the content on the page is to push a lot of cognitive load onto the end user: global filters, drill down modals, grids of charts without context. Like most users, business people hate that shit. And because the production process isn’t in code, the outputs are hard to version control and test—so dashboards break, results are internally inconsistent, and so on, in just the way that software would suck if you didn’t version control and test it.
If I could upvote this a 100 times, I would. I've felt this pain everyday with Looker, Mode, Metabase, every other BI tool that I've tried.
YMMV, but in our experience the vast majority of the hours logged in the 'self-serve' pivot table interface of a BI system come from folks who actually do know SQL and have the word analyst in their title.
When you look at session data on non-technical people doing things with those pivot table interfaces, they are almost never doing the 'complex exploratory analysis' that BI vendors advertise. They are either doing sequential lookups of individual records, or they are putting together a simple data pull so that they can do something in a spreadsheet.
We think we can address the bulk of these use cases by providing two components: a lightweight pivot table, and a 'download to excel' button. These would be components like any other chart or graph. Outputs.
We think a pivot table is a nice output for some situations, we just don't think your data team should have to use a pivot table interface to produce the whole reporting system.
Can’t wait to try this out.