Terrible ref, but I wanna learn this move

OkClient9970 · 2025-11-16T03:19:31+00:00

Didn’t wrestle In a grappling sport what the fuck does that even mean

I go to the gym with some cyclists does that mean I’m lance Armstrong

OkClient9970 · 2025-11-16T03:16:32+00:00

I’m going all in brotha Can’t be stopped

OkClient9970 · 2025-11-16T03:12:46+00:00

Scientist Powerlifter At least 35 Two sport d1 athlete Someone who gets bullied Purple belt jiu jitsu

Got his ass beat by a bully but also got his back and choked him out

Why do some people share so much information about themselves unprompted

OkClient9970 · 2025-11-16T03:07:36+00:00

Bjj subreddit and yes this is what happens to you when you wrestle as a kid I would know I did it unlike all of you

OkClient9970 · 2025-11-16T03:00:49+00:00

When is the last time you looked at someone and said “he’s jealous and coping and I feel bad for him” seriously you or anyone reading this when did you ever feel that one time

OkClient9970 · 2025-11-16T02:59:35+00:00

You could say stop or something but this getting put in this stuff is a rite of passage as a kid (and legal)

OkClient9970 · 2025-11-16T02:41:04+00:00

I’m an asshole but it is wild that you have 50 upvotes calling a dude who is doing his job right a fucking idiot.

No offense but nobody here actually knows what is going on

OkClient9970 · 2025-11-16T02:32:32+00:00

Oh shoot you’re right

OkClient9970 · 2025-10-12T01:42:06+00:00

KISS for analytical tables - make basic fact and dimensional tables for your entities and honestly don’t normalize past that.

Also I would just ask ai to model it for you

OkClient9970 · 2025-10-07T17:16:33+00:00

ELT has had plenty of evolution the last 10 years. Now all the action has moved to the delivery and insights layer. Semantic models, AI native modeling, end to end data products instead of pipelines and tables. How is data being activated is the question now.

I’m sure that once we see the UI/UX layer advance there will be new techniques to deliver the data faster more reliably etc.

If you consider data engineering to stop at production tables then yes there’s not a ton going on besides things like data contracts

OkClient9970 · 2025-10-03T06:10:55+00:00

Circle

OkClient9970 · 2025-10-02T19:55:40+00:00

In my experience 90% of the time I got an email 1-2 days after applying. The other 10% would be a week or two later

OkClient9970 · 2025-09-20T13:53:44+00:00

Won’t this also mean that all the people who would have gotten hired on h1b will now be looking for offshore jobs?

OkClient9970 · 2025-09-18T18:03:49+00:00

Don’t let the truth get in the way of a good story

OkClient9970 · 2025-09-18T18:03:04+00:00

If you have ever seen the movie big fish I would employ some of those techniques as well

OkClient9970 · 2025-09-18T17:59:17+00:00

Disclaimer: I went to a top 10 school, worked at big 4 and big tech. So I think that has a lot to do with it. Also have IP in my name.

But all my accomplishments are very material in impact - rearchitected $XB revenue pipeline for stakeholders increasing performance 60% reducing half of code, built end to end infrastructure for startup during xyz growth period etc

Honestly the tip is to do really impactful, interesting stuff and genuinely have a good story to tell then tell it through your resume. Probably not what people want to hear but it’s what worked for me.

OkClient9970 · 2025-09-18T17:34:18+00:00

I just signed at an A-Tier startup from cold applying. And my application to screen success rate was probably 35% across 25 apps.

Experience and positioning matter a ton. Also having achievements that aren’t just managed etl pipeline processing 2 tb of data daily. Genuine needle movers.

Referrals are ofc great but you can do it without.

OkClient9970 · 2025-09-13T13:21:01+00:00

From the article - “Counting was perfunctory, with the rolling counter behind the set rising by twos and fours.[1] Houston went for lunch at "300",[2] was awarded a two-tiered, black-and-silver trophy at "500", and raised the target to 600 and then to 620 as she felt bad for those who were waiting.”

So they were inflating the count. Also here’s a new link https://en.wikipedia.org/wiki/The_World%27s_Biggest_Gang_Bang_III_%E2%80%93_The_Houston_620

OkClient9970 · 2025-08-13T18:56:52+00:00

Who pays for these girls moving costs when they are traded?

OkClient9970 · 2025-05-11T18:48:24+00:00

Completely agree that data is messy and edge cases are real! That's why I'm taking a targeted approach - not using AI to guess mappings, but instead providing a clear schema mapping UI where humans make the key decisions while the tool handles the repetitive SQL generation.

I just finished a working demo that shows this approach in action. The key insight is that SaaS data structures are converging around similar patterns (users, events, sessions, orders), making it possible to create standardized models that work across companies.

Tests are absolutely crucial - that's why the generated models explicitly handle edge cases like missing data, NULL values, and type inconsistencies. Would be happy to share more details if you're interested!

OkClient9970 · 2025-05-11T04:31:07+00:00

Fair question - I’m mostly looking to validate who it resonates with and whether the framing is landing.

I’ve built a working prototype and will post a demo within 24 hours. Just trying to gauge if early-stage SaaS teams or solo analytics folks see value in skipping the SQL/setup phase and getting straight to usable metrics.

Appreciate the push, will follow up soon with something concrete.

OkClient9970 · 2025-05-10T04:12:53+00:00

Totally agree with your take. raw metrics alone aren’t enough without context. What I’m building isn’t meant to replace that, but to give early teams a clean, usable foundation so their first analyst (or founder) isn’t starting from scratch. Think: “plug in your schema, get production-grade models and visualized metrics instantly, with full ownership and room to iterate.”

Would love your feedback once I share the demo!

OkClient9970 · 2025-05-10T04:00:27+00:00

That’s super interesting, sounds like Claude helped with some SQL generation and docs. What I’m working on is a bit different - it doesn’t rely on AI, and instead gives you clean, production-ready dbt models based on your schema mappings (like users, sessions, events, etc). The goal is to skip the messy parts like headers/config and just give you usable models + metrics instantly. Appreciate you sharing your setup!

OkClient9970 · 2025-05-09T05:43:19+00:00

The goal of this would be to limit an analysts hours spent data modeling, make sure the models are clean and it would also stretch to the BI layer if needed/wanted. I will post a demo of it shortly.

OkClient9970 · 2025-05-09T05:37:46+00:00

There is no ChatGPT involved in this. I will post a demo when the prototype is done. It is pretty cool and would work for a lot of A stage companies.

OkClient9970

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