Unlock the Power of dbt Cloud for Data Teams

In today’s digital age, technology dominates the economic landscape. Organizations that want to remain competitive in the virtual and digital marketplace must adopt the new technologies that come into existence. This is especially true as our society becomes increasingly digitally integrated and reliant on technology. The era of technology and information has been upon us for at least a couple of decades now, but what uniquely makes the virtual economy so viable is the growing presence of digital natives in the consumer base. A digital native grew up alongside world-changing technologies like the internet and smartphones. Because of this, they don’t perceive what time was like before these tools existed.

Kids are growing up in a fundamentally different society today, making them think, socialize, and even enter the workforce in fundamentally different ways. Understanding the modern-day consumer is a significant part of the online marketing, advertising, and sales puzzle. As such, consumer data has become one of the most valuable resources that an organization can obtain. However, collecting consumer data is only one-half of the equation. Making use of it is a whole different story.

Utilizing consumer data in day-to-day operations is a pursuit that has created an entire industry of technology and software dedicated to just that. This all started back in the 1970s with ETL technology aimed at breaking down the data silos that would inevitably develop within an organization’s infrastructure. However, centralizing the data in a single space gave rise to several other issues.

Yet another technology was invented to make centralized data more accessible and operational. This, creatively, was given the name reverse ETL. As the name suggests, this software functions as the reverse of ETL. Rather than centralizing data in a warehouse, reverse ETL aims to distribute consumer insights from the warehouse to other SaaS platforms used for growth, sales, marketing, and development. This is all part of the modern data stack.

However, another key element to the modern data stack is the DBT Cloud.

The IDE

The DBT Cloud is a cloud-based program that allows data engineers to bring the best data analytics practices into real-time queries. DBT stands for data build tool. This feature is critical to include in any modern data stack.

One of the elements of the DBT Cloud is the IDE or integrated development environment. This feature alone saves both time and money in the development process. Data engineers can perform live query checks on their various models in the integrated development environment. This way, they can ensure that their queries and models function correctly throughout development.

Without the IDE, developers would have to continually copy their work from a text-based document into the query-checker and have to run the entire model. This is simply an inefficient development process. Not to mention, this makes it much more challenging to find the errors in complex models. Compared to the ability of the IDE, a developer can run checks as they press a button and incrementally save their progress to identify errors when they occur.

Simplified Orchestration Processes

The DBT Cloud isn’t just helpful in developing queries and data models against the data in the warehouse. Still, it also brings easy, simple, and smooth orchestration functionality to the fingertips of data engineers and other users.

While in the development phase, models are run manually, which doesn’t work when scaled. DBT Cloud makes scheduling your models to run and update regularly as easy as can be. This way, everyone relying on fresh data has it exactly when needed.

Continuous Integration

Continuous integration is another integral aspect of DBT Cloud that makes it worthwhile. However, developing models with constant integration can be arduous when the entire model has to be tested with every update. No matter how minor. This is why DBT Cloud came out with a Slim CI feature.

The Slim CI feature allows users to develop models and add them incrementally to ongoing development projects. Then, rather than testing the entire model, the Slim CI only tests the additional models being added.

This saves time, money, and a whole lot of stress.

Wrapping up on the DBT Cloud

Data is only projected to continue climbing in value. As such, the organizations and brands that implement systems and processes to optimize and operationalize their collected data will have a competitive advantage over those that don’t. Bringing the DBT Cloud into your modern data stack will help your developers create functional data models, programs, and queries that inform and empower the entire operation.

FAQs

What is dbt Cloud?

dbt Cloud is a hosted platform that allows data teams to build, deploy, monitor, and discover data assets at scale, ensuring trusted data and efficient workflows.

How does dbt Cloud accelerate data product development?

dbt Cloud standardizes data modeling processes, automates testing and documentation, and provides built-in version control, enabling faster and more reliable data product development.

What are the collaboration benefits of dbt Cloud?

dbt Cloud supports various development environments, promotes governed collaboration, and allows data developers and analysts to work together seamlessly, improving overall productivity.

How does dbt Cloud ensure data trust?

dbt Cloud offers detailed lineage, logs, alerts, and built-in testing frameworks to maintain data integrity and trust, ensuring that data products are reliable and accurate.

Can dbt Cloud be integrated with other tools?

Yes, dbt Cloud integrates with various platforms like GitHub Actions, Tableau, and other data visualization tools, providing a comprehensive data ecosystem.