The Fundamentals of dbt Cloud
Our world today is dominated by technology in almost every facet of life. From our social lives to our professional ones, technology is becoming a bigger and bigger part of everyday life each and every year. The past few years, specifically, contributed to a major push in professional communities to embrace technology that would enable remote working environments. These environments proved extremely productive and beneficial to both the individual remote employees, and the collective company or organization. Individuals reported higher levels of productivity and a better sense of work-life balance as they were saving time, money, and energy on things like daily commutes. Companies were seeing more engaged employees who were maintaining consistent levels of productivity. Between the success of a remote working environment and the instant access to a global market that smart technology and the internet represent, there is no doubt that these will remain integral aspects of building, running, and operating a business or organization today.
In the same vein, data is also extremely valuable in today’s digital marketspace. More and more consumers are spending their free time online in one capacity or another. Whether this is through the use of social media, or streaming entertainment like film and TV, or even online gaming. This isn’t all, either, many consumers shop online, get news online, and use the internet to learn or educate themselves as well. This consumer data can be extremely powerful for brands if they’re’ able to utilize it properly. This is where dbt, or a data build tool, comes in handy, especially for start-up organizations and smaller data teams.
No matter where your organization is though, the dbt cloud can be an excellent addition to any modern technology stack.
A Dedicated IDE
One of the first things to note about the dbt cloud is that it comes with its own IDE, or integrated development environment. Traditionally, building a dbt project would happen through a text editor program on your computer. While the workflow that this offers is typically very easy and straightforward for data engineers, it does come with certain downsides. One of the main downsides to developing a dbt project in this manner is that there’s no way to check your work as your build. Instead, once you’ve finished a block the whole thing has to be copied into your query runner to make sure that everything works just as it should.
The integrated development environment that comes with the dbt cloud allows for users to check their work as they go with a simple key-command that conducts a preview of your current query. This saves time and energy, and creates an incredibly easy, and innate editing process. If something doesn’t work when you preview your query you can dig into the issue right there and then, instead of down the road when you have an additional 50 or more lines of config you would have to sort through. The integrated development environment also comes with a few other features that are designed to improve the accuracy with which you’re writing your dbt code. By typing a double underscore, “__”, the dbt cloud will use its auto-complete feature to help you with standard snippets of dbt code. This can save the user even more time and make the whole writing process simple and efficient.
User Friendly Orchestration Tools
After getting the dbt code written and working as you want it to, it needs to run on a regular basis. During the development phase, these queries are triggered manually, but that’s ineffective for practical implementation.
As such, the dbt cloud comes with user-friendly orchestration tools that make it incredibly simple to schedule regular iterations of a dbt query. Many organizations have these operations run overnight so that teams come to work in the morning with freshly updated data with which they can work.
Useful in Many Modern Technology Stacks
While the dbt Cloud eccles in the context of small data teams and start-up organizations, it really is useful in just about any modern technology stack. There are a variety of ways that organizations can implement different features of dbt Cloud into their pre-existing stack.
Great for Small Data Teams
The reason that the dbt Cloud is revered in the context of small data-teams and start-ups is because of the way the membership packages are tiered. The free-tier for a single developer-seat is beyond generous and offers a single user a wide-variety of dbt tools that make running queries and writing dbt code a breeze.
Other packages price per developer seat, and there are enterprise level packages as well which come with additional features like role-assignment.
The Future of dbt Cloud
Although the dbt Cloud isn’t perfect by any means, it offers brands a lot of value in its current state. More promising though, is that it’s a service that seems dedicated to continual improvement, and it keeps getting better each and every year.