The Transformational Power of dbt in Analytics

Data

The Transformational Power of dbt in Analytics

Many of us have seen the recent news that dbt received another round of funding to continue growing its platform. For those unfamiliar with dbt, now is the perfect time to give you an introduction and discuss how it can play a role in your technology stack.

What Is dbt?

dbt is short for data build tool. dbt allows users to transform or model data inside their warehouse and helps data teams work like software teams. It leverages many of the same concepts of a typical software engineering team, such as version control, continuous integration and deployment, and unit testing. These features provide an open framework for making data more dependable and reliable in the same way software development and deployment has. Much as the modern software team has evolved to encompass DevOps and Test-Driven Development, the modern data team is also evolving to encompass more roles. This new role combines the skills of a data engineer with the mind of a business analyst, resulting in the appropriately called analytics engineer.

What Is an Analytics Engineer?

Here is a good description of the analytics engineer:

Analytics engineers provide clean data sets to end users, modeling data in a way that empowers end users to answer their own questions. While a data analyst spends their time analyzing data, an analytics engineer spends their time transforming, testing, deploying, and documenting data. Analytics engineers apply software engineering best practices like version control and continuous integration to the analytics code base.

Using dbt, the analytics engineer is responsible for the “T” in the ELT process. Transformations are key when developing any data product for business users to leverage. If only all our data were neat and clean… With dbt, analytics engineers can quickly build data models by writing simple SELECT statements. dbt compiles these statements and executes them against your data warehouse. By building a robust data model, the business can be sure that the data and transformations driving the decision-making process have been tested and documented.

How You Can Leverage dbt Inside Your Team

Adding dbt to your technology stack can be very useful for delivering value to members of your team. One of the questions we see organizations ask is, “How can I use dbt within my team?”. Luckily, we can help you solve that problem. When evaluating whether dbt is the right solution for you, it is important to understand where it fits in your stack and what other platforms you should pair with it to quickly leverage insights. Contact us to set up a time to talk about your current data strategy and what direction you would like to see your team head. We’d love to discuss options and help equip you with the best solutions and strategy to meet your goals!

Stay tuned for future blogs on the specifics of dbt by following us on LinkedIn and other platforms!

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More About the Author

Colin Murray

Data Engineer
Exploring dbt Cloud vs. Core In our previous post, we briefly introduced dbt and an emerging role on modern data teams called an analytics engineer. If you’ve had a ...
The Transformational Power of dbt in Analytics Many of us have seen the recent news that dbt received another round of funding to continue growing its platform. For those unfamiliar ...

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