Reviews from AWS Marketplace
0 AWS reviews
-
5 star0
-
4 star0
-
3 star0
-
2 star0
-
1 star0
External reviews
External reviews are not included in the AWS star rating for the product.
Speed, Power, Control at low cost
What do you like best about the product?
the best achievements we reach with DBT is the time reductiong in ETL process .
What do you dislike about the product?
if you have to manage complex process you need to create a big number of models
What problems is the product solving and how is that benefiting you?
ETL time duration has been reduced and also our DWH cost decrease with this redcution
- Leave a Comment |
- Mark review as helpful
Great tool - fast development experience
What do you like best about the product?
Time saving of having fully integrated tool - faster development experience than managing my own IDE, query tool and command line/git
What do you dislike about the product?
git branches that are deleted still stick around for some reason, dark mode glitches and becomes light mode on some tabs, SQL preview window glitches and freezes
What problems is the product solving and how is that benefiting you?
Collaborating on data pipeline design and creation of data assets
Great software to manage transformations
What do you like best about the product?
Eady to use, saves the need for a data engineer to manage our transformation pipelines, very scalable for our organization, integrates great with other tools in our tech stack
What do you dislike about the product?
dbt Cloud UI can be clunky and time consuming to load; without good data governance or guardrail, you can run up high data warehouse costs and a multiplication of tables and views
What problems is the product solving and how is that benefiting you?
dbt helps us manage all our data transformations in a single location and to schedule jobs that produce all our production tables for analytics purposes (dashboards, reports, models)
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
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
showing 111 - 120