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dbt modernizes my pipelines
What do you like best about the product?
I love how the types of materializations are well documented and presented as a journey toward various stages of dbt maturity - dont start with incrementals. I love how dbt is SQL driven, even when introducing macros.
What do you dislike about the product?
I can't seem to keep the dbt Cloud and dbt Core documentation separate when I arrive from a google search or forum. I would also love to talk about bringing dbt Cloud Enterprise into the GCP Marketplace to make it easier to recommend to my customers.
What problems is the product solving and how is that benefiting you?
dbt modernizes my data platform by enabling me to treat my data pipelines and warehouse as code, templates, and DAGs. Without dbt, I have to broaden my toolset to accommodate other non-SQL tools, which can lead to less DRY code.
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dbt is amazing!
What do you like best about the product?
dbt is a great tool for creating declarative pipelines to transform data while making automation easy and intuitive. There are so many benefits to choosing dbt, but what I like best about dbt is integrating data quality checks in data pipelines.
What do you dislike about the product?
As the project gets larger and larger, so do the yml files and other project-level configuration files, which makes it less readable.
New dbt Cloud IDE usability features are essential to make this better. (Autocomplete, error checking etc.)
New dbt Cloud IDE usability features are essential to make this better. (Autocomplete, error checking etc.)
What problems is the product solving and how is that benefiting you?
dbt makes Git integration and CI/CD easier as we don't need to think about defining our frameworks for these. Also dbt packages are extremely helpful.
all the things I missed when working in data warehouse
What do you like best about the product?
integration with git
lineage
autogenerated documentation
templating possibilities
lineage
autogenerated documentation
templating possibilities
What do you dislike about the product?
adds complexity for users not familiar with git
lack of code formatting by default
lack of code formatting by default
What problems is the product solving and how is that benefiting you?
it allows collaboration for outside stakeholders
adds documentation and lineage, testing and source freshness
adds documentation and lineage, testing and source freshness
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.
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.
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