We use the solution to deal with data transformations inside different organizations.
dbt Platform
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Overwhelming when it comes to optimize and centralize your big data.
What do you like best about the product?
1. The documentation it generates when all the models are designed. It clearly defines which intermediate and final layers are connected to each other.
2. The incremental model runs greatly helped me in optimizing large data models as I was dealing with billions of rows of data.
2. The incremental model runs greatly helped me in optimizing large data models as I was dealing with billions of rows of data.
What do you dislike about the product?
I did not come across any difficulty in learning DBT as it was pretty basic and I also applied SQL fluff to streamline my coding. As a user, I did not find much difficulty in operating through dbt.
What problems is the product solving and how is that benefiting you?
Previously, I was using GBQ for creating thousands of lines of stored procedures and so many tables were interconnected inside of it. It was pretty difficult to determine which tables are made up of what.
When I started using DBT, I was able to quickly determine and find the staging and intermediate layers for the purpose of creating a final layer and the documentation it creates was awesome.
I am talking about dbt docs generate and dbt docs serve.
When I started using DBT, I was able to quickly determine and find the staging and intermediate layers for the purpose of creating a final layer and the documentation it creates was awesome.
I am talking about dbt docs generate and dbt docs serve.
Deal with data transformations with flexible learning curve and handle big data workloads
What is our primary use case?
How has it helped my organization?
You need some knowledge. Dbt has a more flexible learning curve than other tools. You need some experience to handle big data workloads but with less experience, you can get started.
What is most valuable?
They help us orchestrate different transformations. With Dbt, you can automate the orchestration of transformations without thinking too much.
What needs improvement?
SQL statements that beyond DML, are not possible. Currently, they are not possible in Dbt. Having more features in SQL statements will support us.
Another issue is the terms of data ingestion because Dbt requires sources to be defined, and you need to handle data ingestion with other tools. So having a data injection tool integrated within dbt will be awesome.
For how long have I used the solution?
I have been using dbt for three years.
What do I think about the scalability of the solution?
It's very scalable because it's open source. You can spin up different EC2 or different compute instances to run VVT. We have 14 professionals using this solution. I rate it a nine out of ten.
How was the initial setup?
I store procedures calling within dbt statements. You can only use a selected statement in debt. If you want to use more advanced or more complicated SQL features, they are not supported right now by Dbt, so that can be a challenge.
What's my experience with pricing, setup cost, and licensing?
It is cheap because dbt is open source. If you compare the pay-per-service of Dbt with the open source option you can manage. We are managing the solution, when we were acquiring service from them. It was also cheap compared with the engineering cost that implies managing the the infrastructure.
What other advice do I have?
I have had the opportunity to teach one of the tools to level entry engineers because it's easy to learn and easy to maintain. It's pretty useful.
It depends on the architecture and the amount of company's data or the people that I'm going to advise. If you're starting a data engineering team and you don't have a lot of big data workflows, I would recommend Dbt. I recommend our tools for more advanced workflows but for starting, I recommend 100% Dbt.
Overall, I rate the solution a nine out of ten.
Our analytics are more reliable and efficient
What do you like best about the product?
Im thrilled to explore how dbt revolutionizes our work by delving deeply into the data world. Its a total gamechanger providing remarkable simplicity in formulating and utilizing data code within our warehouse. When it comes to version control dbt streamlines the entire process ensuring a smooth experience and maintaining crucial data models for analysis.
What do you dislike about the product?
It would be good if dbt made it easier for new folks. It can do a lot with data stuff, but figuring how to set it up and use all its cool things can feel hard at first. More intuitive guides or a simpler way to learn the basics would make it nicer for people just starting with data changes.
What problems is the product solving and how is that benefiting you?
In my role as a data management specialist, I have seen how dbt changed how we change data. It keeps changes same under control and tested well guaranteeing how exact our analyzing is. The automatic things of dbt have helped us work better freeing our team for strategic things not manual data work. This made us more quick and able to answer with data that helps our group make choices based on data.
Using dbt has improved accuracy and collaboration in our data projects
What do you like best about the product?
In my role I absolutely love using dbt - its the ultimate tool for transforming data with ease. It effortlessly integrates into our current systems making our analytics work a breeze. Were all in on dbt because it excels at data transformation and organization boosting our efficiency and collaborative efforts tremendously.
What do you dislike about the product?
It would be fantastic if dbt could enhance it's toolkit for visual data modeling. At present its heavily focused on coding but integrating a more visual approach to working with data would undoubtedly elevate its utility especially for individuals who gravitate towards graphical methods for data analysis.
What problems is the product solving and how is that benefiting you?
As data enthusiasts we consider dbt our everyday superpower dramatically enhancing our data analysis while effortlessly managing complex data changes. Its our goto tool smoothing our data work and ensuring our insights are as sharp as a tack allowing us to make informed decisions to propel our business forward.
Good tranformation tool for data engineers : Complete SQL Magic.
What do you like best about the product?
DBT has been game changer in the realm of data analaytics for me.
Its One of standout feature is abilty to transform data in warehouse itself it makes it lightning fast
The powerfult modular sql based approach to define transformation makes it fall in love for data engineers.
Its automatic document generation feature is simply outstanding.
Its SQL based moduler approach makes it easy for implementation.
Its One of standout feature is abilty to transform data in warehouse itself it makes it lightning fast
The powerfult modular sql based approach to define transformation makes it fall in love for data engineers.
Its automatic document generation feature is simply outstanding.
Its SQL based moduler approach makes it easy for implementation.
What do you dislike about the product?
If someone is not well-versed in SQL it will be dificult to implement it initially.
The main feature it doesnt have is inbuilt scheduler.
The scheduler will make it complete transformation tool for data engineers.
The main feature it doesnt have is inbuilt scheduler.
The scheduler will make it complete transformation tool for data engineers.
What problems is the product solving and how is that benefiting you?
Ability to create moduler, version control models ensures my transformation code is well maintanable and scalable.
Its version control feature makes it very easy for developers to collabrate.
Its feature of auto generating insights/ documents makes it outstand.
Its version control feature makes it very easy for developers to collabrate.
Its feature of auto generating insights/ documents makes it outstand.
Dbt Cloud is exactly what a lean and mean team needs!
What do you like best about the product?
Pipeline execution management is easy!
- Task dependancies are easy to manege
- Excution logs are deatiled
- Alerting is easy
- Initial setup is super easy
Convenient dev enviroment
- The git integration enables to easily spin up development environemnts, check out a development branch and run you code in a production like environemnt
- Task dependancies are easy to manege
- Excution logs are deatiled
- Alerting is easy
- Initial setup is super easy
Convenient dev enviroment
- The git integration enables to easily spin up development environemnts, check out a development branch and run you code in a production like environemnt
What do you dislike about the product?
Would be nice to be able to set up several Snowflake connections for the same project.
What problems is the product solving and how is that benefiting you?
It reduces the hassle and the overhead around data pipeline automations. Makes it easy to keep a lean and mean team, yet have everything you need for a production data pipeline
DBT is a great tool that has saved our data team a lot of time.
What do you like best about the product?
Model creation and CI/CD are top features.
Thanks to DBT we have reduced the inconsistency of our data models and we reduced the number of manual tasks performed by the team.
Thanks to DBT we have reduced the inconsistency of our data models and we reduced the number of manual tasks performed by the team.
What do you dislike about the product?
The documenting process could be improved.
Since we started using DBT, the load on our data warehouse has skyrocketed. Tools that optimize queries would be greatly appreciated.
Since we started using DBT, the load on our data warehouse has skyrocketed. Tools that optimize queries would be greatly appreciated.
What problems is the product solving and how is that benefiting you?
We use DBT for data consolidation and transformation. DBT is a key piece of our data infrastructure.
Every piece of information gathered from the different sources using fivetran is processed using DBT: from marketing events to information about our car's performance (we a car leasing company)
Every piece of information gathered from the different sources using fivetran is processed using DBT: from marketing events to information about our car's performance (we a car leasing company)
DBT
What do you like best about the product?
Cloud.dbt has proven to be an invaluable tool for our data modeling and analytics needs. Its seamless integration with cloud platforms, user-friendly interface, and robust features have significantly streamlined our workflow. The platform's automation capabilities have allowed our team to focus more on deriving insights from data rather than dealing with intricate modeling processes. The collaborative environment enhances team productivity, making it a standout solution for organizations aiming to elevate their data analytics game. I use it daily.
What do you dislike about the product?
Remember me during sign in doesn't work.
What problems is the product solving and how is that benefiting you?
Automation of jobs and syncing with database
Best opensource data orchestration tool
What do you like best about the product?
- Easy to use and deploy for someone with SQL background
- Great community of support
- Easy to launch and maintain
- Can support data quality testing
- Great community of support
- Easy to launch and maintain
- Can support data quality testing
What do you dislike about the product?
- Complex transaofrmations which require python gets harder
What problems is the product solving and how is that benefiting you?
- Ability to run data quality tests at scale and minimal costs
- SQl tests easy to write and for ETL using SQL
- SQl tests easy to write and for ETL using SQL
An awesome tool for easy Data Transformations
What do you like best about the product?
One of the best things about dbt is that because it's an Sql-based platform, anyone ranging from a Data Analayst to a Data Engineer can easily implement and deploy Data Pipelines. It provides integrations with any different data sources like postgres, Snowflake, Bigquery etc along with features like CI/CD and version control.
What do you dislike about the product?
Currently dbt only focuses on the transformation aspect of a data pipeline. It can also focus on Data quality.
What problems is the product solving and how is that benefiting you?
dbt has enabled engineers to write a data pipeline in an SQL based format instead of writing huge codes using the same big data technologies, thus enabling anyone on the data team to setup and build their own pipelines. It also provides its own cloud platform where we can run those jobs and get data as per request.
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