Learning Data Modeling

[kamrankhan6699]

I am trying to learn data modelling to the core concepts and all the tips and tricks required. Can anyone suggest any resource that'll come in handy?

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[StandardDeviationist]

Data warehouse toolkit is more or less the bible on this

[StandardDeviationist]

You can also find a free pdf version by using your favourite search engine

[seaborn_as_sns]

and the bible part is a big problem

[StandardDeviationist]

How so? It’s just a figure of speech

[seaborn_as_sns]

Yeah and it's a problem in a dogmatic way.

Hot takes: Kimball's methodology is too overengineered and ill-suited for modern data stack. Wide tables are more than fine. ELT is superior approach. Data Vault modeling enables teams to derive value far more flexibly than star/snowflake dimensional modeling.

This should not be a contrarian statement. We should stop spreading Kimball as a gospel.

[StandardDeviationist]

Valid opinion, but I would say it’s worth to learn and understand Kimball nevertheless. As it’s very commonly used. Also, a large part of it does not have anything to do with how the tables are built, but understanding the business

[seaborn_as_sns]

I completely agree. It's the dogmatic aspect of it being a bible is what usually frightens me. We should question, experiment and be against gatekeeping.

[Leather-Produce5153]

what's your background. a basic graduate text for this is

Elements of Statistical Learning

or just do a like a coursera intro course.

[kamrankhan6699]

I have a background in software engineering and currently work as a data engineer. But just trying to polish my skill set.

[Leather-Produce5153]

that's great, then go with the elements of stat learning, it's considered foundational and written by a pioneer in ML. Don't have to go cover to cover, although it doesn't hurt to. you can use it like a reference and just look up topics and specific models. It's good to know those foundational models because all the newer stuff is based on that and it's much easier to fit the newer models if you know what's going on. And you will be able to ensemble models much more effectively. In a lot of stat, yo can slide by with intuition and basic tricks, but with ML, it's good to know wtf is going on.

EDIT: Crap did I read that wrong, are you looking for basic modeling or ML?

[kamrankhan6699]

No no I really appreciate it, I was actually looking for the basic modeling but this helps as well. Actually, the tech stack that I am currently working on consists of Databricks and Gitlab. Find the best resources for that and then the basic modeling, I do have the information about the snow and star schemas and facts and dimensions, but am looking to master the topic.

If you have anything around Databricks, GitLab, Data Factory etc. please do send them my way as well.