Seeking Advice on Streamlining Data Models in dbt

Help
1

Hi everyone,

I’m relatively new to dbt and loving the journey so far! I’ve been working on a project where I need to streamline my data models for better performance and maintainability. I have a few questions and would appreciate any advice or suggestions from the community:

  1. Best Practices for Model Organization: How do you structure your dbt models and directories to keep everything organized and efficient?
  2. Optimizing Query Performance: What are some tips or techniques you use to optimize the performance of your dbt models? Are there specific strategies that have worked well for you?
  3. Managing Incremental Models: I’m planning to implement incremental models. What are the common pitfalls to watch out for, and how can I ensure they run smoothly?
  4. Documentation and Testing: How do you keep your models well-documented and tested? Any tools or practices you recommend?

I have been through these resources/articles Data modeling techniques for more modularity splunk interview questions, and they are quite informative but I wanted to learn more from community members.

I’m eager to hear about your experiences and any resources you can point me to. Thanks in advance for your help!

Best Regards :slightly_smiling_face:

2

Hey! I’ll point you to a couple things right off the bat. For your first question, I highly recommend reading up on data modeling techniques. The Data Warehouse Toolkit (by Ralph Kimball) is a great resource for learning how to model data. It’s not so dbt-specific, but this is based on decades of learning how to model data for usability from a business perspective. As for documentation, get familiar with the dbt-codegen package as this will help you generate yaml much faster for your models, increasing the likelihood you document them fully!