Udemy

Learn DBT from Scratch

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  • 15,497 名學生
  • 更新於 8/2020
  • 可獲發證書
4.4
(2,783 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
3 小時 3 分鐘
教學語言
英語
授課導師
Jeremy Holtzman
證書
  • 可獲發
  • *證書的發放與分配,依課程提供者的政策及安排而定。
評分
4.4
(2,783 個評分)

課程簡介

Learn DBT from Scratch

Complete guide to Learning DBT including connecting it to a Data Warehouse

What you'll learn

Welcome to this course, Learn DBT from Scratch. DBT lets you build a system of transformations on your data, with tests, scheduled runs, multiple environments, flexibility, and more all without needing a team of engineers to set up and manage your workflow. By the end of this course, you will have:

  • set up DBT locally and on the cloud

  • connected DBT to Snowflake (or a data warehouse of your choice)

  • create your own SQL transformations on data

  • test your transformations

  • snapshot your data to keep track of how your data changes over time

  • learn DBT best practices

In this course, you'll be presented with the summarized information you need so that you can quickly get DBT implemented in your data pipeline (or in a brand new, data warehouse).

Why you should learn DBT

DBT is not one of the first technical skills most Data Scientists or Analysts think to learn. It’s not as exciting as machine learning algorithms, and it’s not as easy to show off as a fancy data visualization.

But DBT is an absolutely fundamental skill for any Data Scientist or Analyst due to all of its capabilities. Because DBT is so flexible, there are almost an endless amount of ways you can integrate DBT into your data architecture. Some features that DBT provides you that all Data Scientists and Analysts should be using in their work include:

  1. Creating consistent aggregations for your analysis in a single location

  2. Consistently testing your transformations and underlying data

  3. Running your data transformations on a schedule

  4. Test your code in a DEV environment

About DBT

DBT is pioneering modern analytics engineering. DBT applies the principles of software engineering to analytics code, an approach that dramatically increases your leverage as a data analyst. They believe that data analysts are the most valuable employees of modern, data-driven businesses and they build tools that empower analysts to own the entire analytics engineering workflow.

課程章節

  • 6 個章節
  • 31 堂課
  • 第 1 章 Introduction
  • 第 2 章 Connect DBT and Snowflake
  • 第 3 章 Getting Started with Models & Tests
  • 第 4 章 Deploying and DBT Cloud
  • 第 5 章 Advanced Topics
  • 第 6 章 Best Practices

課程內容

  • Connect DBT to Snowflake or another database
  • Create SQL transformations that use consistent logic
  • Test SQL transformations and underlying data
  • Run transformations on a schedule
  • Add snapshots for slowly changing dimensional tables
  • Test your code in a dev environment
  • Learn DBT Best Practices
  • Advanced DBT Topics

評價

  • A
    Adarsha Mukherjee
    1.0

    He didn't explain the setup properly, even the setup is only done for Mac. There is no information for Windows user. You will have to go on youtube or other portals to learn to setup... I choose this cource to save time, but it seems it is taking more time for research

  • A
    Abiroop Mohan
    5.0

    Short and sweet course, it goes through the important information about dbt.

  • S
    Scott Matthews
    3.5

    It's mainly because the material is a bit out of date with the setup, and the fact that some tools were installed ahead of time makes the install steps seem more straightforward than they actually are. I expect to be able to see the warts of the process to fully know what I'm getting into.

  • S
    Swarnali Datta Ghosh
    4.5

    nice course with good explanation of most concepts

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