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dbt is transformational (pun intended)
What do you like best about the product?
dbt is intuitive to learn and use. The community makes implementing dbt feel like joining some kind of social club where everyone just wants you to succeed which is so rare. The documentation makes it super simple to translate an idea into action.
What do you dislike about the product?
dbt makes writing code very accessible to people which is a double-edged sword. A lot of people new to dbt take a shoot first, ask questions later approach which leads to a lot of technical debt and cloud computing expense down the road.
What problems is the product solving and how is that benefiting you?
Cleaning data and translating business logic into version-controlled models to maximize the efficiency of the data team and deliver value faster.
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dbt makes analytics engineerings great and fun
What do you like best about the product?
I love how it aligns with the analytics engineering practices and it can make our team do better analytics
What do you dislike about the product?
Since my team is using dbt CLI, I dislike that I have to test my queries on the data warehouse first and then change the code to use the Jinja template. It's like I'm doing the work twice.
What problems is the product solving and how is that benefiting you?
- It helps my team organize the code better and makes it able to reuse the existing models.
- The documentation and lineage graph the dbt generates save us a lot of time.
- The tests really make us more confident in data quality.
- The documentation and lineage graph the dbt generates save us a lot of time.
- The tests really make us more confident in data quality.
DBT is a very intuitive tool with advanced features that'll help scale your analytics teams
What do you like best about the product?
Breaking down reusable CTEs into separate tables/views increases scalability and consistency.
What do you dislike about the product?
Some of the config features like making tables incremental can be a little confusing and tough to get right on the first try.
What problems is the product solving and how is that benefiting you?
Allowing the Analtyics team be self-serve on typical engineering tasks. We are also able to dictate source-of-truth definitions by building the reusable CTEs
Very useful and easy to use.
What do you like best about the product?
I can create project and manage with git and also I can connect my db easily I can create secrets and manage them for each project.
What do you dislike about the product?
Actually I have nothing to this question.
What problems is the product solving and how is that benefiting you?
I can manage my data and connect to databeses
Powerful and Easy to Use ETL Tool
What do you like best about the product?
The best part of DBT is the power that comes with its ease of use. Once you play around with DBT a bit and get a handle on it, it can do all sorts of great tricks with just a SELECT statement and a little bit of Jinja.
What do you dislike about the product?
DBTs only weakness right now is I find the examples in the documentation to be a little simplistic, not covering all the options like the examples in a Microsoft help page would. Luckily, for more complicated use cases, you can get help in their Slack community, which is quite lively and helpful.
What problems is the product solving and how is that benefiting you?
DBT is helping us normalize several data sources together into one master model and then exposing slices of that master model in the form of views we base our exports on. We have over 2k models between putting the sources together and then sharing the slices.
dbt adds so many features to SQL that I hadn't even realised were missing
What do you like best about the product?
There's a lot that I really like about dbt, particularly in the way it automates so much of the 'grunt work' out of transforming data. It's now tough to imagine how we handled refreshing our data warehouse before dbt!
Specifically I am a fan of how dbt:
- Works out dependencies rather than you having to stay on top of which models need to be run before others
- Automates testing, running tests on a schedule rather than when you remember to run the testing!
- Handles version control, allowing you to keep track of changes
- Provides a straightforward way of handling separate development and production environments, so you can see the impact of your changes before making them live
- Has a very active community of Slack users and package developers
Specifically I am a fan of how dbt:
- Works out dependencies rather than you having to stay on top of which models need to be run before others
- Automates testing, running tests on a schedule rather than when you remember to run the testing!
- Handles version control, allowing you to keep track of changes
- Provides a straightforward way of handling separate development and production environments, so you can see the impact of your changes before making them live
- Has a very active community of Slack users and package developers
What do you dislike about the product?
This is quite minor, but with documentation it can be a bit onerous to keep .yml files up to date, as the formatting needs to be exact and it is not always obvious when something is wrong, for example, with the amount of tab spacing.
What problems is the product solving and how is that benefiting you?
dbt has essentially "automated the boring stuff", letting us spend less time on boilerplate SQL work and more time thinking about the design of our models and how they best serve our reporting needs.
Avid longtime customers
What do you like best about the product?
Foundational data modeling for reporting in external tools. Testing and data correctness framework. Data-as-code continious deployment and automation. Documentation.
What do you dislike about the product?
A lot of repretitive data crunching that is somewhat hard to eliminate. Even with incremental models, subsequent models still make a full data transform. More caching / incremental tools for downstream models would be appreciated.
What problems is the product solving and how is that benefiting you?
Customer data and behavioral analytics. Unifying data from multiple sources for ease of access. Creating snapshots and time series data from mutable tables in various sources.
Streamlines SQL Development
What do you like best about the product?
After years of working with cumbersome ETL flows, dbt's modular approach makes it simple to change only a small portion of a large process without breaking anything. Having version control with SQL is a game changer.
What do you dislike about the product?
There is a learning curve to working with dbt, like any new solution/process, but the upside is worth it.
What problems is the product solving and how is that benefiting you?
dbt's approach to making SQL code clean and DRY has greatly improved our workflow and code.
The best tool for data engineering on Snowflake!
What do you like best about the product?
I appreciate the ability to generate a DAG quickly. This capability is beneficial for developers to extend the data warehouse while understanding what may be impacted downstream. The recent improvements to the cloud IDE have been substantial.
What do you dislike about the product?
The cloud IDE is going through a complete revamp, and during that time, there have been some glitches in how it operates. There have also been a few outages over the past few months, but nothing of major consequence.
What problems is the product solving and how is that benefiting you?
We use DBT as part of our tech stack for our embedded analytics product. It has allowed us to go from no data warehouse to a stable and agile data warehouse in weeks.
Fantastic SQL orchestrator that bridges the gap between analysis and programming
What do you like best about the product?
* All models, configurations and tests stored as version controlled code
* OSS as well as a managed SaaS-service
* Easily overviewable lineage & dependency trees
* OSS as well as a managed SaaS-service
* Easily overviewable lineage & dependency trees
What do you dislike about the product?
* There are some hidden complexities/nitty-gritty details you need to figure out before dbt becomes a powerful tool
* Parts of the documentation lack example(s) or have examples using legacy/old standards
* Parts of the documentation lack example(s) or have examples using legacy/old standards
What problems is the product solving and how is that benefiting you?
* dbt collects and orchestrates all transformations that before were scattered between analyst's own Drives, embedded within tooling or otherwise just laying around. I think this is one of the most powerful things dbt has done for us thus far.
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