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My learningDBT Interview QuestionsLesson 15
What is the difference between a seed and a source

Lesson 15

What is the difference between a seed and a source

A seed in DBT is a small CSV file managed inside the project and loaded into the warehouse, while a source is an existing raw table already present in the warehouse. Seeds are created by the team, while sources come from external systems.

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Curriculum

20 lessons · 39m

0/20 lessons done39m left
  1. 0101:56

    What is DBT & Why Is It Important?

    01:56

  2. 0201:58

    Does dbt do the E, the L, or the T in ELT — and why does that distinction matter?

    01:58

  3. 0302:04

    DBT Core vs Platform vs Fusion Engine

    02:04

  4. 0402:01

    Why DBT Is an Analytics Engineering Tool

    02:01

  5. 0501:58

    Main Files & Folders in a DBT Project

    01:58

  6. 0601:54

    DBT Prerequisites Before Installation

    01:54

  7. 0701:55

    DBT Works With Your Data Warehouse, Not Instead of It

    01:55

  8. 0802:06

    DBT vs Traditional ETL Tools (Informatica & SSIS)

    02:06

  9. 0901:52

    When would you NOT use dbt?

    01:52

  10. 1001:58

    DBT vs Apache Airflow: Can They Work Together?

    01:58

  11. 1102:02

    Purpose of dbt_project.yml & Key Sections

    02:02

  12. 1201:54

    Sources vs Models in DBT

    01:54

  13. 1301:53

    Declaring and Referencing Sources in DBT

    01:53

  14. 1401:42

    Seeds in DBT: What They Are & When Not to Use Them

    01:42

  15. 01:54

    What is the difference between a seed and a source

    01:54

  16. 1602:24

    Source Freshness in DBT: Configuration & Testing

    02:24

  17. 1701:58

    Organizing 200+ Models in a Maintainable DBT Project

    01:58

  18. 1802:03

    Staging / Intermediate / Marts Folder Convention in DBT

    02:03

  19. 1901:55

    What is a dbt model, and what is its basic structure?

    01:55

  20. 2001:55

    What does the ref() function do, and why is it critical to dbt?

    01:55