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DBT with a Silicon Valley Engineer

Learn how modern data teams leverage dbt. Build maintainable analytics models and validated data pipelines hands-on. Master core concepts of analytics engineering with a practical focus. This course is for those who want to take their data career to the next level 🚀

186 learners are taking this course

Level Basic

Course period Unlimited

  • altoformula
SQL
SQL
데이타베이스
데이타베이스
데이타모델링
데이타모델링
dbt
dbt
실습 중심
실습 중심
Data Engineering
Data Engineering
data-analysis
data-analysis
Data literacy
Data literacy
SQL
SQL
데이타베이스
데이타베이스
데이타모델링
데이타모델링
dbt
dbt
실습 중심
실습 중심
Data Engineering
Data Engineering
data-analysis
data-analysis
Data literacy
Data literacy

What you will gain after the course

  • Understanding the complete workflow of how modern data teams work with dbt

  • Organize and extend complex SQL into structured models

  • Practical analytical engineering sense that can be applied immediately to real work

  • Improving Data Reliability through Testing and Documentation

🚀 Beyond SQL, Real Analytics: dbt Analytics Engineering That Works in Practice

In this course, you'll learn how to build a modern data analytics environment using dbt.
Going beyond simply writing SQL queries, we cover the process of designing maintainable analytical models and creating
reliable data pipelines through testing and documentation..

You can understand the core concepts of analytics engineering used by actual data teams in a practical way, connecting modeling, testing, and documentation in one unified flow.

#SQL, #Database, #DataModeling, #dbt, #HandsOn

🏢 What fields is this mainly used in?

The dbt and analytics engineering approaches covered in this course are widely used in the following fields.

  • 📊 Data Analytics Team (Analytics / BI)

  • 🧠 Analytics Engineer

  • 🏗️ Data Engineering Organizations

  • 🏢 Modern data stack environments from startups to large enterprises

  • ☁️ Cloud-based data warehouses (BigQuery, Snowflake, Redshift, etc.)

🎯 Course Planning Background

In practice, many teams still struggle with
"SQL that works but nobody trusts"
"analysis queries where no one knows who created them."

I also repeatedly experienced these problems in the field,
and have been adopting dbt and analytics engineering approaches as the solution.

This course is designed to help you understand and apply dbt not through theoretical explanations, but exactly as it's used in real data teams. It's created to help those who want to turn data into 'manageable assets' beyond just SQL.

👉 What you'll learn

🔑 Analytics Engineering with dbt

You'll learn the complete workflow of how modern data teams use dbt to build analytical data. You'll understand how to transform ad-hoc SQL into reusable and manageable analytical models. You'll clearly define dependencies between models and design a structure that refines data step by step.

🧪 Testing & Documentation for Trusted Data

You'll learn how to transform data from "plausible-looking results" into trusted analytical assets. Leverage dbt's testing features to validate data quality and build an analytical environment that the entire team can understand through automated documentation.

Modern analytics starts here.

📌 Notes Before Taking the Course

🖥️ Practice Environment

  • Operating System and Version (OS): Windows, macOS, Linux, Ubuntu

  • Tools Used:

    • dbt Core (Open Source)

    • Python 3.9 or higher

    • Docker & Docker Compose (for unified practice environment)

    • Visual Studio Code or your preferred code editor

  • PC Specifications:

    • CPU: 2 cores or more

    • Memory (RAM): 8GB or more recommended (minimum 4GB)

    • Disk: 10GB or more of free space

📘 Learning Materials

  • Lecture slides (PDF / PPT)

  • Source code for hands-on practice (entire dbt project)

⚠️ Prerequisites and Important Notes

  • Basic SQL usage experience is required.

    (SELECT, JOIN, GROUP BY level)

  • In the course, we will be using PostgreSQL in a Docker environment.

    Don't worry if Docker is still unfamiliar to you! 😊

    I have a free Docker course available, so if you need it, feel free to check it out and you'll be able to follow along quickly. 👉 https://inf.run/KkNw9

🧩 Great to take together

A practical, hands-on course that allows even SQL beginners to start easily and immediately apply what they learn. ✨

Pulling data with SELECT, connecting with JOIN, organizing with GROUP BY, and more

Let's learn only the most frequently used features in real work, easily and enjoyably! 📊

We'll minimize complex explanations,

"Ah, this is why SQL is important!" The course proceeds with realistic, immediately understandable examples. 💡

Data Analyst, Developer, Data Engineer…

No matter which path you choose, SQL is an essential skill. 🚀

With this one course, you'll build a solid foundation,

I'll help you develop the data intuition to solve problems on your own in real-world situations! 🔥

Recommended for
these people

Who is this course right for?

  • 👨‍💻 Those who use SQL but always feel their analysis structure is lacking

  • 🧩 Those who want to make analysis results more reliable

  • 🚀 Those who want to learn how modern data teams work

  • 📈 Those who want to advance their data career to the next level

  • 🔥 For those who want to break free from ad-hoc SQL

Need to know before starting?

  • ✅ Basic SQL experience is sufficient.

  • 📊 If you understand SELECT, JOIN, and GROUP BY, you'll be able to follow along without any problems.

  • 🚀 If you have experience in data analysis or data engineering, you can understand it more quickly.

Hello
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Curriculum

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21 lectures ∙ (2hr 26min)

Course Materials:

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