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Chinese cigarette website with great UX

There’s no good way to play pocket jiggities @bradowen

To be fair they could have done an experiment on a transaction that typically requires a person in the loop. Rather than choosing a vending machine which, already, does not require a person in the loop for the transaction.

Interesting choice of Pandas in this day and age. Maybe he’s after imparting general concepts that you could apply to any tabular data manipulator rather than selecting for the latest shiny tool.

The market can stay irrational longer than you can stay solvent.

Agreed, but maybe the step change there is refactoring the data model, not continuing to author “hairy” sql via LLM that’s all fine until it breaks… and you end having to mend the nastiness back into compliance the ol’ fashion way

What is the human need to bash SQL at all costs? At its core, such a simple syntax, yet its so powerful at aggregating/manipulating tabular data and the like. Instead we’d rather declaratively say what we want in a more verbose/disjointed way… fascinating

Do you have any data to backup the claim: “vast majority of companies understand suck cost fallacy.”

I’m assuming you meant “sunk” not “suck”. Not familiar with the suck fallacy.

So sad. Humans are so smart and yet soooo dumb.

I feel like this is more an example of:

“We filtered first instead of reading an entire table from disk and performing a lookup”

Where both OLAP and OLTP dbms would benefit.

To your point, it’s clear certain workloads lend themselves to OLAP and columnar storage much better, but “an endless sequence of misbehavior” seems a bit harsh .

Exactly. “Everything is urgent” is the great burden of our time lol

I love a semantic layer as much as the next guy...

Pivoting a decent sized BI shop toward using one instead of splashing the same SQL all over the place is *tough*. It's one of those: "the analyst could have been building important report for director and you want them to create re-usable logic??? we'll do that later, get report done now. Just copy/paste that SQL over here"

This is how you end up with the the 1000 model, "the numbers don't match up", hot mess situations that gain momentum and are hard to slow down.

I always do that when working with a new cloud provider. I spend our Series A as fast as possible after which we can optimize cloud spend!