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One of the best data transformations tool on the market
What do you like best about the product?
What I love about DBT is the ease of use! You only need to know SQL to do all the data transformations you need
What do you dislike about the product?
The only downside that comes to mind is the fact that there are a lot of tools you can use to work with DBT, and finding the right one might be tricky
What problems is the product solving and how is that benefiting you?
We automated all our data warehouse transformations with the help on DBT
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One of the best Transformation product
What do you like best about the product?
Ease of use and setup
Transformation logic can be written easily
Python model makes it very much flexible
Transformation logic can be written easily
Python model makes it very much flexible
What do you dislike about the product?
Macros error debugging gets clumsy at times
What problems is the product solving and how is that benefiting you?
Helps me to write transformation logic easily
structured DB modelling
structured DB modelling
dbt is a great tool, I wouldn't want to be without it
What do you like best about the product?
Most helpful is how dbt sorts out dependencies for you. Using references in your models, you can tell immediately if a column name change has caused a problem downstream. The DAG graph is fantastic, particularly in the dbtCloud IDE as it updates immediately. Adding basic tests is easy, leading to increased levels of confidence. I know I can run and rerun things without causing problems. If tests pass we're good to go. Freshness tests help make sure that nothing is run if upstream data is not present. This has helped us considerably recently. And exposures, linking to external reports that use the data, is really useful.
What do you dislike about the product?
Creating a job in the dbtCloud interface and having it default to an hourly schedule. We've only had one minor mishap, but that could be costly with BigQuery. Unless I've missed a setting, that should be off by default.
I don't use the Web IDE. Personal preference, I don't want to switch editors. But the lineage graph is awesome, and seeing the compiled alongside the editor is a great feature.
I don't use the Web IDE. Personal preference, I don't want to switch editors. But the lineage graph is awesome, and seeing the compiled alongside the editor is a great feature.
What problems is the product solving and how is that benefiting you?
Getting data under test so that we know the data makes sense, not just that it has been loaded. The freshness tests have increased confidence that reports are ready to send from our BI tool. We have a history of many similar queries doing the same work. We're using dbt to find and eliminate that duplicated work.
Awesome product + word of mouth
What do you like best about the product?
DBT solves the most fundamental and pressing problems that a small scale, agile data engineering team face. In particular it gives you the ability to take control of your datawarehouse, you decide, manage, develop, test, deploy the end to end steps of the warehouse, regardless of the technology you use.
What do you dislike about the product?
How it scales with complexity, size and maturity of the company. I struggle to see how this will progress into enterprise level solutions, but I could be surprised !
What problems is the product solving and how is that benefiting you?
A variety of technical problems: e.g. how to structure, how to run, how to deploy the logic underpinning the datawarehouse.
Some team problems: e.g. how do I ensure that various members of the data engineering team collaborate, share, build together
The benefits are clear, with 1 or 2 senior engineers that know dbt, you can build a data warehouse from scratch within a few months, with a budget 10 times smaller than what was possible previously.
This is clearly a technological rupture, there is a before and after dbt in the world of data warehouses (for startups )
Some team problems: e.g. how do I ensure that various members of the data engineering team collaborate, share, build together
The benefits are clear, with 1 or 2 senior engineers that know dbt, you can build a data warehouse from scratch within a few months, with a budget 10 times smaller than what was possible previously.
This is clearly a technological rupture, there is a before and after dbt in the world of data warehouses (for startups )
The perfect tool for the job
What do you like best about the product?
The cloud IDE is well-designed and executed, with great attention to detail. The overall design of the tool exactly meets the need of the analytics engineering problem.
What do you dislike about the product?
I dislike nothing, but two areas for future development might be (1 )column-level data lineage and (2) data-diff tools, both of which could help with evaluating the impacts of a model change before deploying it.
What problems is the product solving and how is that benefiting you?
Adding an abstraction layer on top of SQL allows me to write code to generate my transformations instead of coding them directly, saving time, adding power, and improving reusability.
dbt is the single most powerful tool in our arsenal
What do you like best about the product?
dbt allows us to create a federated data model including information from all of our operational platforms. As a result, we've eliminated swivelchair tasks, latency in report reconciliation, and blindspots in our ability to create a 360 degree view of our clients.
What do you dislike about the product?
I really don't have any complaints. To the extent that anything has been difficult, it's because I'm using something that is inherently a very complex tool. That said, the fact that a layperson without actual engineering experience can build with dbt says a lot about how well it'd built.
What problems is the product solving and how is that benefiting you?
Like all businesses, we have data in many, many platforms and none of them are capable of reporting comprehensively on our business. dbt allows us to federate the data across those platforms and gives us a single data model to operate from.
dbt has fundamentally changed how I work with data
What do you like best about the product?
After working with BigQuery in the marketing and digital analytics space for a few years, we embraced dbt about 1,5 years ago. It has completely transformed our thinking about data modeling, quality, accountability of data products and documentation. From an analyst's perspective, dbt brings necessary engineering principles into data work and helps build data products for the longer term.
What do you dislike about the product?
There are always aspects that can be improved. The ecosystem has seen such fast growth that the space has become fragmented. Many tools built on top of dbt or are tightly integrated could be part of a more extensive suite.
What problems is the product solving and how is that benefiting you?
Organizing data transformations in BigQuery and building high-quality data marts for business use cases
dbt Cloud is the perfect tool for our data transformations
What do you like best about the product?
We have highly complex SQL transformations. dbt allows us to engineer them properly, writing DRY, modular code and using CI/CD. Jinja in dbt allows us to work with SQL data models as objects. We use Fivetran as the E and L in ELT, and Fivetran has an extensive library of dbt packages to provide transformations for many of our data sources.
What do you dislike about the product?
dbt Cloud's IDE has been improving, but still doesn't have many of the features coders have come to expect from IDEs. And the orchestration available in dbt Cloud is limited.
What problems is the product solving and how is that benefiting you?
Without dbt to store and maintain our SQL transformation workflow, we would have a mess of SQL scripts that would be very difficult to manage. Without dbt, we would need to write something that had dbt's functionality.
UI based Version Control and ETL Orchestration
What do you like best about the product?
DBT Cloud lets users set up transformations and orchestrate code runs from a UI-based IDE in the cloud for users who aren't as familiar with using the command line. By leaving engineers to do the coding rather than spending time digging through documentation, our team could reach functionality faster and with less fuss than expected. The ability to test in a safe environment by default before you push your changes to live makes version control easy for users not familiar with git principles.
What do you dislike about the product?
The cloud-based IDE has a long-ish startup time (30 seconds or longer) and locks you out of editing while it syncs after you save a file. This leads to a little bit of frustration when making minor edits across multiple files. Some other minor frustrations related to the Cloud IDE come to mind, like how column names aren't sensed while you're typing, leading the user to write out column names that could be easily polled during the lineage population. In addition, the testing documentation was a little confusing, leading to me trying different things to get it to work. In the end, I learned that you have to prefix the name of a test model with "test_" to get the orchestrator to see the model as a test. However, after a couple of speed bumps, most issues I have turn out to be minor and do not impact the product's overall usefulness.
What problems is the product solving and how is that benefiting you?
DBT Cloud has allowed us to migrate from one ETL partner and re-create our transformation files with version control and replicability in mind first and foremost. Additionally, for users who aren't familiar with command line interfaces, we can spin up new users and share work easily while everyone can push to the same deploy environment.
DBT is top-notch.
What do you like best about the product?
DBT makes developing a data warehouse fun. My favorite is the testing functionality. I am no longer anxious that reports are sent with incorrect data!
What do you dislike about the product?
I don't love the UI. However, I develop mostly locally.
What problems is the product solving and how is that benefiting you?
Data testing, documentation and warehousing.
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