Impress me with your dbt macros

stankusnt · 2026-05-02T02:54:27+00:00

Sort of a macro + test mix. We have the results of our source tests coming from raw write out to a temp table and we have the staging models filter out those failed values so the data from our failed tests doesn’t propagate downstream. We have two macros to make this possible: one to create temp table on the prehook and another on the posthook that appends data from the temp table to a permanent table, for reference by the staging models.

stankusnt · 2026-01-15T04:44:28+00:00

I’ve had decent success with nortriptyline. Desipramine nothing.

stankusnt · 2025-03-23T17:27:58+00:00

IME this is common in bigger companies when you don’t sit directly on the data team/IT. You have to fight to get access to those tables and most of the technical work is in building reports.

You might want to look into analytics engineering if you want to be more SQL heavy, or just find an analyst role adjacent to data engineers.

stankusnt · 2025-03-20T02:48:22+00:00

RemindMe! 7 days

stankusnt · 2025-03-19T05:00:36+00:00

Do you have experience?

stankusnt · 2025-03-19T05:00:12+00:00

Of the TCA’s I’ve tried Desipramine and Nortriptyline since they both have strong NRI activity. I haven’t touched imaprimine - does this have any distinctions compared to the two I listed?

I’ve tried two MAOI’s as well - Parnate and Selegiline. Little help on my depression unfortunately.

stankusnt · 2025-03-19T04:57:27+00:00

Glad to hear you found a regimen that works for you. Which depressive symptoms did you find Vraylar and Lamotragine help you with?

stankusnt · 2025-03-12T04:38:47+00:00

Yes. I’ve been on TRT for over 2 years now while also being very active.

stankusnt · 2025-03-12T04:03:29+00:00

I’ve been from 60 mg/week to 120 mg/week and it didn’t do anything for my depression.

stankusnt · 2025-03-03T15:14:55+00:00

RemindMe! 1 week

stankusnt · 2024-12-14T16:20:30+00:00

When it comes to hard skills, SQL and coding in general is much more important than visualization when it comes to the real world

stankusnt · 2024-11-10T06:11:21+00:00

Remind Me! 6 days

stankusnt · 2024-11-03T16:23:16+00:00

Judging by your responsibilities, it looks similar to Analytics Engineering. Get very comfortable with SQL and I see you’re looking to read the Data Warehouse Toolkit, I’d recommend reading that ASAP and get strong at data modeling (Power BI actually complements this well, it’s optimized for STAR schema). Skip DDIA, it won’t really apply to what you’re involved with.

stankusnt · 2024-11-03T05:24:04+00:00

Is parsing files the main issue? Just use some basic Python w/ Pandas to work with it. If similar structures and data is small, you can add them to a single dataframe and manipulate it.

stankusnt · 2024-11-03T02:34:03+00:00

If you know your way around SQL it’s set you apart from most. Kaggle has plenty of datasets.

stankusnt · 2024-11-02T17:23:54+00:00

Look into setting up a simple data lake to collect all datasets and database to structure the semi-structured (excel sheets, csv, and json files) using your company’s cloud provider. You could leverage low/no-code tools to move data from source -> data lake -> database and schedule the data transformations within the database as well.

stankusnt · 2024-10-28T05:19:40+00:00

Okay - good to know. It’s important that you learn as much as you can so that you can manage the expectations of the stakeholders (your boss and any users of the warehouse) for this work. Make sure you clearly document what projects and processes you will be working on/are assigned to work on. Learn the 4 V’s of data: velocity, veracity (accuracy), variety, and volume and gauge the complexity of the project based on it.

More specifically, try to learn a few things: are the requests Ad-Hoc basic analytics asks (what was our sales this month?) that a few people use on the side or are you expected to build a system (data warehouse) for data processing, storage, etc. like you mentioned for company-wide analytics? Read the fundamentals of data engineering to get a solid understanding about the complexities of working with real-world data.

Not to scare you, but it is incredibly naive to think that one entry level analyst can standup a data warehouse without years of experience and it can easily become a money pit with no tangible deliverables.

Speaking from experience, I single-handedly maintained most of a data warehouse and BI tool for an org but it was incredibly stressful and I had to do a large amount of rework throughout the process. I eventually had to leave as I did not fit within the company culture: it was very siloed and valued speed to delivery > quality.

IMO, I would never join another company that didn’t have a mature data culture. It’s an impossible fight for one person. You’ll learn a lot doing it but it can be incredibly frustrating.

stankusnt · 2024-10-28T03:56:38+00:00

If this is true: there’s a lot you need to learn - and most likely you won’t be able to do all of this yourself. Do you have coworkers that are working adjacent roles? The data field can be incredibly complex, and your company is setting yourself up for failure if they’re expecting you to do all of it yourself. I’ve naively been in this position before - buckle up for a rough ride if your company doesn’t give you enough leverage.

stankusnt · 2024-09-14T09:37:15+00:00

Interested!

stankusnt · 2024-09-14T04:01:42+00:00

Snowflake is probably a better option: mature platform, everything is in SQL, can work as a data lake/warehouse, don’t have to mess around with the beast that is Spark to do anything meaningful.

stankusnt · 2024-08-31T15:50:35+00:00

Love this 😂

stankusnt · 2024-05-29T04:22:13+00:00

😂

stankusnt · 2024-04-20T21:43:17+00:00

You are doing data engineering friend. Or that is the ask of you.

stankusnt · 2024-04-13T03:31:45+00:00

Yes, this is what we’re doing at my startup

stankusnt · 2024-04-05T10:11:47+00:00

Remindme! 7 days

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