I love to teach. I post about #dataengineering and #mentalhealth daily. 

Many years of data engineering experience doing growth analytics at Facebook, security infrastructure at Netflix, and pricing and availability infrastructure at Airbnb. 

You can find me by looking up EcZachly on all social networks 

Join my Data Learning Platform https://www.dataexpert.io

Zach Wilson

Databricks is going to win “data” the same way that Meta won “social media” 

They are uniquely positioned because of the convergence of a few trends:

- the death of the data analyst
We are moving away from analytical architectures and towards action-oriented architectures. Instead of “the data engineer does ETL so analysts can look at it” it will be “the data engineer creates context for AI agents to do something” Actions will reduce timelines and speed up business velocity. Humans will no longer be the analytical bottleneck. 

- the crushing of data siloes 
Open table formats like delta and iceberg will make business able to do things that were previously though impossible! We’ll finally have all the context for our AI in one place. Entire business context + Agents = a waterfall of business value! 


I’m launching a paid Databricks boot camp on February 9th. Send me a DM with the word Databricks and I’ll get you the details!

Founder @ DataExpert.io | ADHD | 500k+ followers | Angel Investor

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The first speaker lineup for the analytics engineering boot camp is going to be so amazing! 

These sessions are what truly separates my boot camp from “just another data course”

Data modeling is far from dead! It’s actually more relevant than ever. 

There’s been an interesting shift in the seas with AI. Some people saying we don’t need to do facts and dimensions anymore. This is a wild take because product analytics don’t suddenly disappear because LLM has arrived.

It seems like to me that multi-modal LLM is bringing together the three types of data:

- structured

- semi-structured

- unstructured

Dimensional modeling is still very relevant but will need to be augmented to include semi-structured outputs from the parsing of text and image data.

The necessity for complex types like VARIANT and STRUCT seems to be rising. Which is increasing the need for data modeling not decreasing it.

It feels like some company leaders now believe you can just point an LLM at a Kafka queue and have a perfect data warehouse which is still SO far from the actual reality of where data engineering sits today

Am I missing something or is the hype train just really loud right now?

I'm doing a live with Karan Dwivedi to talk about a cybersecurity boot camp that is launching on January 9th! 

This boot camp has an amazing capstone project where you do all of these on a company server!
- threat modeling
- detection engineering
- preventative controls 

Don't miss this webinar tomorrow!

January 9th Cybersecurity Boot Camp Webinar

I build maintainable and scalable software that brings value.

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The Battle

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Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Zach Wilson's LinkedIn Performance

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