dbt Platform
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dbt for data pipelines
What do you like best about the product?
dbt is excellent due to its wide use of macros and the ability to transform data using SQL, an analyst-friendly language. Given this we can train analysts to read dbt and understand the logic behind our data transformations, limiting the amount of work we need to do explaining data decisions or documenting logic.
What do you dislike about the product?
I wish that dbt was more integrated with other data tools. It seems that a lot of data tools (fivetran, monte carlo, hightouch) are designed with dbt in mind but dbt never seems designed for these tools. It would be nice to have more accessibility within dbt, allowing us to create alerting and etl processes easier.
What problems is the product solving and how is that benefiting you?
Dbt allows us to transform data using SQL and then run this data daily to provide fresh data to analysts. With this data we are able to make business decisions ultimately impacting our bottom line. We also use dbt for minor tests to make sure our data is accurate and clean.
Data Scientist
What do you like best about the product?
DBT is an easy to use too for anyone who knows SQL. Their IDE is wonderful and you can easily spin it up in no time. As a Data Scientist, doing modelling in DBT saves me hours of work and helps me provide an opportunity to others to focus on a more self serve analytics
What do you dislike about the product?
DBT is a great tool but there are a few things missing from it. Direct connection to postgres SQL. Mixing of different sources and more convinent ways of build test and macros.
What problems is the product solving and how is that benefiting you?
Dbt helps us build models for a lot of different complex queries that get used. DBT helps us compile massive queries into tables or views and helps with the flow.
dbt infrastructure has helped us build a data warehouse with a firm foundation
What do you like best about the product?
I love it's self sustainability and the ease of implementation and documentation
What do you dislike about the product?
upgrading dbt versions is sometimes a hassle
What problems is the product solving and how is that benefiting you?
dbt is making it possible to very specifically organize our data and make it very easily accessible
Good product to transform raw data and pipeline it to analytics and business needs
What do you like best about the product?
What I use the most is the documentation feature. It is very robust and complete, which helps me understand where the features I use daily come from and how they were built.
What do you dislike about the product?
I'd say there is a learning curve to start using it which could be smoother. Some basic guidelines on the basics would help a lot.
What problems is the product solving and how is that benefiting you?
Understand how features from the tables are built
Makes data transformations easy to maintain
What do you like best about the product?
Maintaining data transformations are easy with SQL- and git-based workflow. Integrates nicely with Big Query.
What do you dislike about the product?
IDE is not perfect but improving. Git support lacks some basic functionalities.
What problems is the product solving and how is that benefiting you?
Maintaining our data pipelines is easier with dbt than other tools or techiques I've tried.
dbt is very intuitive to use and works great in our data tool stack
What do you like best about the product?
dbt cloud's structure and the ease of transforming the data without worrying about the warehouse connection. Also being able to see the lineage easily to understand the connections.
What do you dislike about the product?
sql help could be much more improved and also showing when there is a false syntax before having to compile or run the preview because there are many times that you need to go out of the platform just to check sql syntax
What problems is the product solving and how is that benefiting you?
transformation of that in a structural way where you have control over the lineage greatly and surfacing reliable models that can be exposed to consumers directly
Efficient, easy to use and reliable for development
What do you like best about the product?
Fast development times and ease of use are my two favourite qualities of dbt. It allows our team to build and test new sql models very quickly, and even less experienced team members with basic knowledge of sql are able to contribute.
What do you dislike about the product?
With large complex models tracking column lineage can be tricky. Especially as fields go through many layers of transformations, identifying where certain data quality issues are arising can be challenging. I realise this is not an easy problem to solve but column level lineage would be super useful at speeding this process up.
What problems is the product solving and how is that benefiting you?
The fast dev times allow us to efficiently accommodate business changes into the logic of our data transformations. As a relatively small data team of 8 serving an org of 600, keeping up with changes to the business is vital for us to be able to work on other high-value data projects.
Newbie to dbt
What do you like best about the product?
Easy to set up
SQL based
UI is intuitive
SQL based
UI is intuitive
What do you dislike about the product?
Lack of logs/metadata on job runs, the area around that isn't strong
What problems is the product solving and how is that benefiting you?
We are able to model our data for Looker outside of looker, so no need for PDTs etc
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.
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.
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