dbt Platform
dbt LabsExternal reviews
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Powerful Features and Git Integration, but Error Messages Need Improvement
What do you like best about the product?
DBT provides valuable features for rapid software development, and what I appreciate most is its seamless integration with Git. Its modular design, which includes the ability to build reusable models, conduct code reviews, and generate automatic documentation, is excellent. Additionally, I am impressed by its capability to define and run quality tests, which further enhances the development process.
What do you dislike about the product?
When a DBT run fails, the error messages displayed in the terminal are quite generic. I find this frustrating because it means I have to spend extra time searching through the logs to figure out what went wrong.
What problems is the product solving and how is that benefiting you?
It solves many problems, especially in terms of data trust, and improves integration, The method runs seamlessly and speeds up processes. We went from hundreds of disorganized scripts to a logical and maintainable pipeline structure.
dbt helps put our data pipelines in order and clear our perspective
What do you like best about the product?
I use dbt daily to handle and transform data models in our warehouse. And it has also become the backbone of our analytics workflow and version controlled, transparent and a breeze to debug. I particularly appreciate how easy it is to modularize sql transformations and to document everything inline so the team knows Why each model does what it does and where this data came from.
What do you dislike about the product?
It can be a bit confusing to set up environment configurations especially when you are working on more than one project or warehouse. As your models grow and that framework layer deepens, your build time can start to slow down and it’s not always simple to identify the bottleneck. Also testing unconventional macros feels a little clumsy compared to writing tests for linear models.
What problems is the product solving and how is that benefiting you?
dbt has brought a level of structure and consistency to the way we transform our data and we no longer have ad hoc sql scripts swimming around. It enables me to catch logic errors in the early stage, ensure data quality through testing and give stakeholders trustable reports. In the end we were able to achieve a better collaboration between our data engineers and analyst and gained much more confidence in our data pipeline.
Transforms SQL with Engineering Principles, But Steep Learning Curve
What do you like best about the product?
I really appreciate how DBT brings software engineering principles to SQL, transforming our SQL into a dependable data model. This helps resolve reporting errors that would otherwise consume a significant amount of our IT team's time.
What do you dislike about the product?
I didt really like that it requires mastering concepts like Jinja and Git.
What problems is the product solving and how is that benefiting you?
By centralizing data transformation logic and raising it to a higher level, this tool becomes essential for any IT team managing a data warehouse. It enables teams to move beyond just generating information, allowing them to create scalable, high-quality data products.
Makes Transforming and Managing Data Models Way More Manageable
What do you like best about the product?
Thanks to dbt, I no longer have to depend on the engineering team to manage and transform the SQL data within our warehouse. It is the first step for me in organizing, testing, and documenting the entirety of our data models. I appreciate that all of this information is in one place in version control. I can track all changes made and the details surrounding each one.
What do you dislike about the product?
Troubleshooting complex dependencies and build errors can be a daunting task. There are occasions when a model fails and it is unclear which upstream change might be the cause. While the documentation is really good, I have found digging into a Stack Overflow or Slack thread to be the answer for some of the more obscure problems. I also find the visualization of lineage in dbt Cloud to be cumbersome.
What problems is the product solving and how is that benefiting you?
Data transformations are far more efficient now with dbt. I no longer need to create custom scripts or deal with disorganized SQL in dashboards, as I can now have a single layer that is testable and maintained for all my transformations. It is quick and dependable to run models in dbt Cloud, which assures me that the data is consistent and current for our business teams.
If its worth it, a data transformer with amazing features
What do you like best about the product?
I appreciate how this tool brings software engineering principles to our data collection process, making it more scalable, auditable, and reliable. I also really enjoy the ability to write straightforward tests that execute automatically.
What do you dislike about the product?
At times, handling very complex transformations or preprocessing tasks requires the use of more advanced Python packages, which means I often need to rely on external solutions.
What problems is the product solving and how is that benefiting you?
At this stage, we are able to use it to reliably scale our business metrics, which provides us with greater speed and is transforming our data stack due to its robust operations and data preparation features. Integration with DBT is seamless, making the entire process smooth.
dbt has become the backbone of my daily data workflows.
What do you like best about the product?
Every day I use dbt to convert raw data for it to be ready for analysis and I especially appreciate that it all involves only SQL and version control—no more messy scripts I like the feeling of writing simple queries and, at the same time, I enjoy the extra modularity and auto documentation. The tests and my transformations running concurrently provide me real confidence in the datasets I provide.
What do you dislike about the product?
When it comes to dbt, the learning curve is quite the challenge and it took me some time to figure out how to set the macros and organize the models in a tidy manner. The task of debugging is also quite a drag and since some of the error messages lack clarity, I end up spending a lot of time on logs. What is more, for large projects, the execution time can be rather long which can hinder the development flow.
What problems is the product solving and how is that benefiting you?
Finally dbt has solved the issue of maintaining the transformations within our team. No more custom code and ad-hoc scripts! I now have a single and unified and transparent process for building and managing pipelines and this has saved me hours and reduced the errors I make and given stakeholders more reliable data. I get to save time every single week!
DBT - From data science to product strategy
What do you like best about the product?
I liked that it completely the way my team and I interact with information. With DBT, I know our customers, usage metrics are accurate and consistent, and its fantastic because it prioritizes functionality to validate our product hypotheses. I loved DBT because it relies on reliable data to make decisions.
What do you dislike about the product?
For team members unfamiliar with engineering workflows, doing so could be challenging.
What problems is the product solving and how is that benefiting you?
Its very useful and benefits us a lot because it takes data-driven product development seriously, and for me its great because it provides reliable analytics capabilities, and honestly, dbt is a worthwhile strategic investment.
We finally brought order to complex metric definitions
What do you like best about the product?
It is very nice that dbt gives us the capability to write out our transformation logic as application code. The process of integrating it with Git implies that our whole team may contribute to data models and track changes without hassles, and revert changes as well. Even the separation of the development and production environment out of the box is a tremendous advantage, so we can ensure that we are testing new things without necessarily influencing live reports. Lastly, the automated documentation generation process has made the data models so simple to comprehend, even to the business users, without ever having the touch a SQL.
What do you dislike about the product?
The initial set up of dbt can be a little fiddly at times and with a mix of operating systems and local database connections. It also lacks its own scheduler, so still we will require an external orchestration tool to carry out our data pipelines. The more advanced Jinja templating and macros proved to be more cumbersome to our team to learn than the simpler SQL.
What problems is the product solving and how is that benefiting you?
Our greatest weakness prior to dbt was inconsistent reporting amongst departments, this contributed to lack of numbers and big debates on the correct numbers between departments. Marketing could report a figure of new customer acquisition and sales could report an entirely different figure and that could slow down decision making. I we have one version controlled definition of all of our critical business metrics since dbt is in place. Such change came to mean that our leadership team trusts the figures implicitly and no longer spends so much time on reconciliation of numbers, but can actually analyze them.
Provides excellent insight into the various sources and streams of data
What do you like best about the product?
I like that it has error-detection capabilities and offers a wide range of connections. It makes it easy to sync analytics data and has a simple user interface that makes data management easy. I was able to easily navigate through the pages using the side panel.
What do you dislike about the product?
I'm satisfied with the platform, I haven't encountered any issues yet. The team has been excellent with us, they've developed an impressive management tool.
What problems is the product solving and how is that benefiting you?
It has allowed us to bring the most relevant data, offering a simple way to securely transfer data. We can obtain important product information, which has helped me save time and effort. I have had an excellent experience with this platform.
Facilitates the implementation of analytical code quickly and easily
What do you like best about the product?
The platform stands out for its exceptional consistency and timeliness. It's intuitive and well-designed, making it easy for our team to get up and running quickly, without the usual complexity or overhead. One of the most notable benefits for us has been its cost-effectiveness.
What do you dislike about the product?
We've had a fantastic experience working with this platform and are delighted with the results. As our data needs have grown, the platform has adapted seamlessly.
What problems is the product solving and how is that benefiting you?
This platform has facilitated the implementation of a new data strategy. Our data team now operates more efficiently, without the complexity of coordinating multiple systems or extraction methods.
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