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Data Build Tool - a tool to build data

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Manage episode 353388209 series 2522423
Content provided by Anthony Moendir & Tim Beeren, Anthony Moendir, and Tim Beeren. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anthony Moendir & Tim Beeren, Anthony Moendir, and Tim Beeren or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
The guest of our show presented the Data Build Tool, DBT, in one of our knowledge-sharing sessions. Especially the fun part is what I recognize when I look at this knowledge-sharing session. The guest of the show presented it in an enthusiastic way and used terms like: the macro functionality makes DBT awesome and Ephemeral is the Unique Selling Point.
What this episode covers
In General

  • What is a Data Build Tool?
  • What problems does it solve?
  • What are the two versions? Cloud, CLI
  • Why is it much more interesting to use than other ETL, transformation tools?
  • Analytics Engineering
  • Explain a bit more in debt the Basics of a DBT project: dbt project data pipeline, data model, tests, macros.
    • Model dependencies
    • DBT-packages ecosystem
  • One of the powers of DBT is Jinja.
    • What could you compare Jinja to?
    • Is it easy to comprehend and learn?
  • Ephemeral (CTE) was the unique selling point for you, why?
  • An engineer enthusiastic about a documentation feature… that asks for an explanation.

Within bol.com

  • Usage started as an experiment, how are we using it in bol.com?
  • Can you share some learnings you and your team had when you started using DBT?

Guests
Sander Boumeester – Software Engineer in the experimentation team.


Notes
On the website of getdbt there's a cool picture that explains the framework really well.

  continue reading

129 episoade

Artwork
iconDistribuie
 
Manage episode 353388209 series 2522423
Content provided by Anthony Moendir & Tim Beeren, Anthony Moendir, and Tim Beeren. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anthony Moendir & Tim Beeren, Anthony Moendir, and Tim Beeren or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
The guest of our show presented the Data Build Tool, DBT, in one of our knowledge-sharing sessions. Especially the fun part is what I recognize when I look at this knowledge-sharing session. The guest of the show presented it in an enthusiastic way and used terms like: the macro functionality makes DBT awesome and Ephemeral is the Unique Selling Point.
What this episode covers
In General

  • What is a Data Build Tool?
  • What problems does it solve?
  • What are the two versions? Cloud, CLI
  • Why is it much more interesting to use than other ETL, transformation tools?
  • Analytics Engineering
  • Explain a bit more in debt the Basics of a DBT project: dbt project data pipeline, data model, tests, macros.
    • Model dependencies
    • DBT-packages ecosystem
  • One of the powers of DBT is Jinja.
    • What could you compare Jinja to?
    • Is it easy to comprehend and learn?
  • Ephemeral (CTE) was the unique selling point for you, why?
  • An engineer enthusiastic about a documentation feature… that asks for an explanation.

Within bol.com

  • Usage started as an experiment, how are we using it in bol.com?
  • Can you share some learnings you and your team had when you started using DBT?

Guests
Sander Boumeester – Software Engineer in the experimentation team.


Notes
On the website of getdbt there's a cool picture that explains the framework really well.

  continue reading

129 episoade

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