4 Benefits of Using dbt Cloud

When it comes to one of the most valuable resources that companies have to help push effective decision-making, it’s data. The problem with data is that it is ever accumulating and as it grows so does the difficulty with which it is available. Data teams, scientists, and engineers work tirelessly to move data through a company and get it where it needs to be. While data is one of the most important factors for helping companies make high-quality decisions, getting that data can be a journey.

While the modern data stack is constantly evolving to help companies overcome this problem, there is one tool that is gaining popularity that you need to know about. Data Build Tool, or dbt Cloud, is one of the most popular frameworks that companies are adopting that makes accessing data efficient and streamlined for small teams.

If you have been wanting to find out more about dbt Cloud and what it can do for your business, here are four benefits you need to know about.

What Exactly is dbt Cloud?

dbt Cloud is a cloud infrastructure that was designed to specifically help improve small data teams’ ability to leverage their time wisely. This tool was designed to help facilitate in the ETL process but specifically focuses on the central step. ETL is a process that has been used for decades when it comes to data integration.

One of the many problems that face business is that not only does data accumulate to a challenging amount, but it also is produced from disparate sources. The data silo represented a problem of too much data from too many disparate sources to be accessible or usable. Companies who struggled to pull their data out of soils and into an integrated, centralized source turned to the modern data stack for their solutions.

ETL stands for Extract, Transform, and Load, which was one of the main tools for solving the problem of the data silo. The dbt Cloud specifically focuses on the T of that process that helps data teams leverage their time for success. It does this by bringing software engineering best practices to the world of data integration, which can free data engineers and scientists from tedious, menial tasks.

1. Dedicated IDE

At it’s heart, dbt is an open-sourced production environment tool with a dedicated IDE. The Integrated Development Environment (IDE), can help streamline the process of queries. This dedicated IDE will compile the query and makes previewing current queries a key command away. This unique IDE helps teams write code efficiently and accurately which can be a huge help when it comes to leveraging a team’s time for success.

2. Easy Orchestration

Orchestration is a crucial aspect of productivity in the data world. The simple truth is, that jobs, pipelines, and tasks take a lot of time and can be very cumbersome without some kind of orchestration tool. While the modern data stack is no stranger to orchestration tools, dbt Cloud integrates easily with Orchestration Workflow tools so that your dbt models can run on schedule. This allows your teams to focus their energy where they need to focus rather than babysit long, tedious processes.

3.  Slim Cl

Another way that dbt meaningfully impacts a data team’s time and helps set them up for success is by adopting ‘Slim’ CI. This allows dbt Cloud to build and test only the modified parts of a project. This can greatly enhance the ability of your team to deploy projects with effective continuous integration in a timely manner. By not re-building and testing models with every change, “Slim” CI can help reduce build times but still provide engineers the confidence they need in their work.

4. A Great Launching Point

Perhaps one of the best parts of dbt Cloud is that it is a great tool to use with no lock-in. This tool is specifically designed to help promote smaller data teams by giving them a data infrastructure that leverages their time for success. However, there are more fully-flushed-out orchestration tools with more features that can benefit larger companies.

As your company grows, it could be that you need to switch to something like Dagster, Airflow, or Prefect. If that is the case, dbt Cloud has no lock-in feature that would keep you from doing this. dbt Cloud is also built with the ability for teams to continue using other features even if you outsource orchestration to another tool.

Conclusion: A Great Addition to the Modern Data Stack

The modern data stack will always be evolving and growing to help businesses tackle the issues that are most relevant when it comes to their data. One of the key factors that make the modern data stack, is accessibility. The more the data stack evolves, the easier it will be to access and analyze data, and this is something that dbt Cloud brings into the picture.