Recent Articles

The traditional approach to data transformation with long SQL scripts, hard-to-trace logic, and lots of manual documentation has always felt like wrestling a monolith. dbt flipped this paradigm with features…

When multiple teams and hundreds of models work in the same dbt project, things can quickly become messy, like overlapping work, broken pipelines, and slow progress. As data platforms grow,…

Snowflake is unmatched when it comes to storing, scaling, and analyzing massive volumes of data with speed and reliability. On the other hand, dbt is best at transforming that raw…

Modern data teams know that stale or outdated data is a hidden liability. In fact, Gartner estimates companies lose an average of $12.9 million per year due to poor data…

If you’ve ever felt like your dbt models are a bit too 'one-size-fits-all'? You’re not alone. A bunch of analytics engineers start with the basics and later realize that tailoring…

If you’re using dbt (Data Build Tool), you’re already on the right track when building scalable data models. As teams grow and projects get more complex, it’s easy for a…

dbt deps is a command that downloads (or updates) the dependencies of your dbt project. In practical terms, running dbt deps will read your project's dependency file, by default packages.yml,…

If you’re just getting started with dbt (Data Build Tool), you’ve probably seen the command dbt init pop up in tutorials or documentation. And wonder, what does it actually do,…

When was the last time you trusted your data pipeline to be clutter-free? In fast-paced analytics environments, redundant compiled files and outdated metadata often lurk behind the scenes, silently inflating…

If you've ever worked on a growing data project, you’ve probably faced this headache: you build a solid dbt model, someone upstream changes a column name or data type, and…