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No brainer when working with batch processing
What do you like best about the product?
It gives you a set of tools to improve data governance and quality. It allows developers to apply many software engineering concepts to create a robust data pipeline.
What do you dislike about the product?
It can be complicated to implement and maintain for a non-technical person or someone who is not proficient in SQL. One of the main limitations for me was that you couldn't run python, which apparently was recently implemented (I haven't tried it yet).
What problems is the product solving and how is that benefiting you?
It helps you to create a robust data pipeline that holds the "source of truth" for data being used for analysis. Using dbt you can automate a lot of transformations and tests, work in collaboration with your peers and write robust documentation.
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The era of shaky SQL templates is over
What do you like best about the product?
DAG execution when rebuilding an entire schema/mart, docs, tests (referential integrity especially), dbt utils and packages (redshift utils especially) and many more.
What do you dislike about the product?
There is little that I dislike, IDE version 2 has improved, one can still over-write default macros in order to achieve custom functionality.
What problems is the product solving and how is that benefiting you?
For instance, my first three months with tool were spent on a migration of all kinds of different sql processes which accumulated over 5 year within the company, now all simplified and unified under one repository. The main problems we solve are staging transformations (used by legacy reporting) and building dimensional schema for self-service analytics as well as embedded analytics.
Gamechanger
What do you like best about the product?
Templating SQL, enabling aspects of data engineering to be treated more like software engineering. CI/CD pipelines. Autogenerated lineage and documentation. Git intergration.
What do you dislike about the product?
I think dbt should be more opinionated on best practices around staging/intermediate/marts and the vocabulary used. Would also like to see further niche coverage (snowflake streams).
What problems is the product solving and how is that benefiting you?
SQL Model lineage and versioning. It makes it much more clearer the upstream sources and downstream impacts of changing any SQL model. Integrated version control and deployment environments also makes rollbacks and testing much easier.
Really helpful for cleaning up data
What do you like best about the product?
The product is really good, but the support documentation and community surrounding the product are really helpful in implementing the product.
What do you dislike about the product?
It takes a lot of training to get competent with the product - not unexpected.
What problems is the product solving and how is that benefiting you?
Orchestrating our data into usable models
Necessary for all data teams
What do you like best about the product?
dbt allows small teams to tenfold their workflow. Small hassle changes are made easier and make sense with dbt. dbt allows you to build on past work quickly and easily. The dbt community is also amazing to be a part of.
What do you dislike about the product?
They're new and relatively young so not all the features are there for an optimized workflow. But they are working on it.
What problems is the product solving and how is that benefiting you?
Metrics alignment, single source of truth for data.
dbt review
What do you like best about the product?
Highly functional SQL transformational tool. Simple to start, but with adequate levels of complexity available to add if necessary. Good documentation.
What do you dislike about the product?
Nothing comes to mind as the product provides a great solution
What problems is the product solving and how is that benefiting you?
Internal data transformation in a cloud warehouse. Very few other products accomplish this as well.
dbt has vastly improved how I get work done. It has changed the data industry and it's wonderful
What do you like best about the product?
dbt gives data teams the ability to version their SQL code, execute that code as often as they'd like, maintain different environments and support multiple users in parallel. All of which require barely any thought from the user. All these functions used to be major pieces of my daily work and with dbt, they are simply memories of when I set up the product. It's wonderful.
What do you dislike about the product?
Once you start getting into some of the advanced functionality of dbt, you can find yourself in what feels like unexplored land. It's an open-source product, so your own creativity is your only limit. However, in those situations finding syntax examples for anything that isn't a main function of dbt is going to be extremely challenging.
What problems is the product solving and how is that benefiting you?
They're constantly improving the UI and user experience in ways that enable my teammates who may have less experience with technical or database maintenance work, to take ownership of their own work projects and exceed.
dbt has fundamentally changed the way we work
What do you like best about the product?
dbt has enabled us to literally re-model a data warehouse from scratch in a matter of months. All the complexities of handling scheduling dependencies, lineage, incremental models, snapshots, and robust, thorough testing have been abstracted away freeing us up to focus on the modelling and design work. If we had built all these ourselves this would have been a years-long project. dbt has also empowered our analysts to build data products without the need for BI Engineers.
What do you dislike about the product?
The primary downside we've all come to experience is that once you've worked with dbt you'll never want to work in an environment that doesn't transform its data with dbt.
What problems is the product solving and how is that benefiting you?
dbt really solved the problem of being able to build a world-class data warehouse rapidly with a small team of analytics engineers. The benefits have been numerous, from having jobs run according to dependencies so we don't have to worry about timing or manually schedule tasks, to built-in testing which means we know about errors before the business does. Our development times are now a fraction of what they were, and the analysts love that they are no longer dependent on a team of data/BI engineers to build and maintain their own models.
Elegant product which both simplifies & improves the role of a Data Analytics Engineer
What do you like best about the product?
DBT is a well-thought-out product which keeps the focus on SQL but also allows proper software engineering techniques to be applied
What do you dislike about the product?
IDE is still inferior to VSCode. Jinja is great but also can be very messy to use. Would prefer a cleaner separation which allows pure Python code to be written.
What problems is the product solving and how is that benefiting you?
Transformation of Business Logic in a Data Warehouse, separation of Development/Test and Production environments with less maintenance than before, allowing the focus to remain on solving business problems. Improved testing and Quality of data.
Analytics Engineering done right!
What do you like best about the product?
dbt's UI is easy to navigate, easy to code in, and easy to run. Documentation is easily accessed and written; I especially like the automatically generated, interactive data model that you can quickly grab when you want to show a stakeholder your work or when you want to discuss a new solution with a colleague.
It resolves many of the pain points of analytics engineering. They are constantly making improvements and implementing new things, but if anything is missing, chances are you can find it in one of the many packages written for dbt. The community is also great, and many resources are provided either there, or in the dbt documentation.
It resolves many of the pain points of analytics engineering. They are constantly making improvements and implementing new things, but if anything is missing, chances are you can find it in one of the many packages written for dbt. The community is also great, and many resources are provided either there, or in the dbt documentation.
What do you dislike about the product?
I sometimes wish there were more "standard" tests in dbt (such as max character length, min character length, max value, min value). One can make these themselves in macros (and potentially some packages could help with this?), but it would be a nice-to-have!
What problems is the product solving and how is that benefiting you?
Data is cleaner, data transformation is simpler, and manual joins are no longer needed. In the end, we've created multiple clean and aggregated tables that can act as a source of truth for analysts. Our data is also better documented.
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