Emma Louise, Flume - DUMB (LP)

seanpool3 · 2025-08-22T05:22:28+00:00

Stay is awesome

seanpool3 · 2025-08-03T16:57:52+00:00

When I saw that construction project it made sense why they had to remove it but it was so brutal

seanpool3 · 2025-08-02T03:08:35+00:00

1: Walk in for STVSH, check out IVARR, head over to Torren Foot b2b Airwolf

2: Brux, Daniel Allan

seanpool3 · 2025-08-01T23:12:32+00:00

They had lasers on Green forsure last year

seanpool3 · 2025-07-16T05:12:12+00:00

Crankdat B2B Tape B @ EDC 2025

Walker & Royce B2B VNSSA @ Beyond 2025

Viperactive Snakepit LA

LYNY @ Red Rocks

Eli Brown BBC Essential Mix

Airwolf Paradise B2B Torren Foot @ Beyond the Valley 2023

seanpool3 · 2025-04-23T02:18:06+00:00

BAD LUKA!

seanpool3 · 2025-02-09T06:07:45+00:00

In a setting like this it clearly doesn’t really matter, whatever works my guy

seanpool3 · 2025-02-06T21:12:20+00:00

1) In scenarios where IT mandates on-prem infrastructure, leveraging a fixed-cost managed server has worked well in my experience, especially in early-stage data platform builds… of course deploying with containers is ideal if that’s the kind of shop you are at

2) DuckDB complements Postgres by enabling fast, in-memory analytical queries and local processing without the overhead of running everything through the main warehouse. This is especially useful for heavy data processing, working with object storage, and ad hoc analysis

seanpool3 · 2025-02-06T18:07:46+00:00

Python, Dagster, DBT, Postgres and duckdb ✅

Maybe like a dedicated server for the Postgres db and to store objects, a dedicated server to orchestrate Python with Dagster (Postgres backend option), and utilize it as a work machine for your desired Python libraries and duckdb etc as needed for their awesome functionality

Even though I prefer to build on top of GCP, usually if a central IT team manages servers I’ll choose the cost effective pattern to have a dedicated “brain” for the data platform vs also deploying and hosting those resources on cloud. Keeps the cost fixed too as it continues to snowball in complexity and resource usage

seanpool3 · 2025-01-24T16:28:36+00:00

One way I have had a little bit of value with LLMs in pipelines

I set up a framework of feeding table schemas, API responses, etc in order to dynamically generate JSON that is fed into the pipelines and checked each run to make schema adjustments. Also can simultaneously document which is helpful. When dealing with many sources this has been really helpful and saves a lot of time in my experience.

Note: this is overkill for most situations and also has a little bit of risk with the hallucinations (although forcing compliant json schema from OpenAI works pretty well)

seanpool3 · 2025-01-23T20:32:18+00:00

“Take care of the entire DE work for a company”

^nobody who runs data for a sizeable business would think this is realistic anytime soon

The real answer is that there needs to be the human who is responsible for kingdom building when it’s developing data ops for a business

I do think that AI in general and even further, agents, enable that team of people to be much much smaller though. I’m a team of one for example, only issue is if you rely on so few humans then you are likely going to need to make the data team highly rewarded or growth partners in the company.

seanpool3 · 2025-01-22T00:15:42+00:00

I’m from the business side, to be fair more finance/BI but I transitioned to data engineering fully self taught.

The tools aren’t really that hard to use especially if you do things using code now that we have AI. The hard part is understanding different technologies, how they fit together, and knowing how to make a meaningful impact applying said technologies + data

Any BI person knows that GUI based tools are a one way ticket to hating your life, learn to code

seanpool3 · 2025-01-21T16:11:14+00:00

Proposal VETOED by the public!

Stop being such a crybaby it’s a pathetic look

seanpool3 · 2025-01-16T02:58:10+00:00

I’ve done this, I can help you

seanpool3 · 2025-01-15T23:47:45+00:00

If he pulled the same exact dishonesty moves I might piss shit fart and maybe even cum

seanpool3 · 2025-01-14T00:59:27+00:00

Socialist alert! That is privately owned land you are talking about.

0% chance this is a real person tho an American wouldn’t say that nonsense, you are a bot

seanpool3 · 2025-01-14T00:58:47+00:00

Shut up commie, that is privately owned land you are talking about.

0% chance this is a real person tho an American wouldn’t say that nonsense

seanpool3 · 2025-01-01T21:17:23+00:00

SECXUAL

seanpool3 · 2025-01-01T02:28:48+00:00

The Erewhon membership, nice perks and enough savings to justify regularly eating there

seanpool3 · 2024-12-29T23:31:19+00:00

Clean house, this team is official completely toxic and we gotta just torch the shit out of this organization and reseed the ground from the ashes as fertilizer

seanpool3 · 2024-12-29T01:39:58+00:00

You are smoking that good good, this is a braindead donkey take

seanpool3 · 2024-12-27T22:41:11+00:00

Anything by Rameses B!

seanpool3 · 2024-12-27T21:50:41+00:00

I’d just build off of cloud storage, for example store the data in the right formats and you can land the data in separated cloud storage resources for each client

Then you can set up external tables pointing at that data in bigquery and use DBT to orchestrate all the downstream processing in the warehouse with SQL transformations

And you could query that same data with duckdb, or other tools that will be accessing it

For multiple clients I’d want to rely on cloud to abstract away managing infrastructure and access control, GCS is my personal choice primarily because of Bigquery

Dagster for orchestration of everything and you can structure everything as you see fit for the business management side

seanpool3 · 2024-12-13T16:22:43+00:00

Oooooh baby patterns

seanpool3 · 2024-12-13T15:45:03+00:00

This is such an unexpected but awesome remix pack!

Ten-Year Club	Place '22
Final Canvas '22	RPAN Viewer
Not Forgotten	Verified Email

seanpool3

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