# Data Modeling Basics

> Data modeling is a critical skill for data engineers, focusing on structuring data to support business decision-making. This lesson covers the three layers of data modeling: conceptual, logical, and physical. Participants will learn how to identify data needs, understand relationships between facts…

- Web page: https://learn.dataexpert.io/lesson/data-modeling-basics
- Program: [The Absolutely Free Beginner Data Engineering Boot Camp starting August 14th](https://learn.dataexpert.io/program/the-absolute-beginner-data-engineering-boot-camp-starting-august-7th-6453.md)
- Access: Free — no enrollment needed
- Length: 9 min video
- Skills: Data Modeling, ETL/ELT
- Academy: DataExpert.io Community Academy

## About this lesson

Data modeling is a critical skill for data engineers, focusing on structuring data to support business decision-making. This lesson covers the three layers of data modeling: conceptual, logical, and physical. Participants will learn how to identify data needs, understand relationships between facts and dimensions, and explore various modeling techniques like dimensional modeling and Data Vault, equipping them with the knowledge to create effective data models tailored to business requirements.

## Transcript excerpt

Data modeling is one of the most important skills that data engineers have to learn. So how is it so important? Well, at the end of the day, data modeling is the structure of the data that we create for businesses because the asset that we produce for businesses is data to make better decisions and data modeling has a bunch of different components to it, and we're gonna talk about each of them. There's the highest level, it's called conceptual data modeling. Then we're gonna be going over the next layer down, which is logical data modeling, and then the final layer that we're gonna talk about is physical data modeling. Uh, in this video, we should be covering all of those. So at the end of this, you should know all the ins and outs of all three types of these data modeling. So let's first talk about the highest level one conceptual data modeling, which is The highest level way of thinking about it is like what data do we need? What data does the business desire, what data do we have access to, what are the sources, where can we find this data? Can we like think about all the relationships of this data like at a very high level? Cause sometimes you might want data in a business, but it's actually unfeasible to get it or it's going to take months and months and months and it's not ROI positive because the time it would take to get the data is more than the value you can get out of it.

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