In this course, you'll dive into the concepts of data warehouse and its lifecycle including
- building data pipelines
- ETL/ELT
- dimensional modeling
- data transformations
- testing
- dashboard
- orchestration
- modern data stack
For this you will be using the following tools:
- snowflake
- snowsql
- dlt
- dbt
- dbdiagram
- dagster
- streamlit
- python
- git and github
- visual studio code
To efficiently follow along in this course, the following prerequisites are recommended:
- fundamental knowledge of python
- virtual environments in python
- fundamental data modeling concepts - conceptual, logical and physical models
- fundamental knowledge in SQL
- version control with git and github
This plan is an overview of the contents covered in each study week.
Note
The study weeks doesn't correspond to the actual weeks, as this course can be taken in different periods.
| Study week | Content | Lectures | Exercise |
|---|---|---|---|
| 1 | data warehouse, snowflake, snowsight, snowsql | 00-04 | 0 |
| 2 | access control, data ingestions, extract, load, dlt | 05-08 | 1 |
| 3 | dimensional modeling, transformations, dbt, | 09-12 | 2, project |
| 4 | dbt continue, testing, streamlit, dashboard, | 13-14 | project |
| 5 | work with project | 15 | project |
Note
The project is only available for students currently enrolling this course. It is found in your course learning management system.
Tip
I highly recommend you to create a passion of yours project based on the contents you learn from this course.