data_warehouse_course

KO | EN

gitlite — search

#python #hacktoberfest #ai #go #docker #nodejs #java #awesome #awesome-list #pytorch #security #ios #mcp #open-source

data_warehouse_course

(★ 22)

A course in data warehouse

data_warehouse_course Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Data warehouse lifecycle course

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

## Plan

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, project info | 05-07    | 1          |
| 3          | dimensional modeling, transformations, dbt,         | 09-11    | 2, project |
| 4          | dbt continue, testing, streamlit, dashboard,        | 12-14    | project    |
| 5          | dagster                                   | 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.

data_warehouse_course

data_warehouse_course Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

data_warehouse_course

data_warehouse_course Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README