I am currently working with Power BI, Tableau, Python, Databricks, Snowflake, and PySpark in the current project. I would rate my overall experience with dbt a nine out of ten.
dbt is easy to use and easy to learn, but it has some limitations that I would love to see mitigated; however, in general, most of my engineers are happy using dbt.My advice for others looking into using dbt is that it is good if you have an organization with engineers who prefer to code and get hands-on, but if you have teams of engineers who prefer a mouse-driven, drag-and-drop type, less technical coding environment, other tools might be more appropriate. I rate dbt overall an eight out of ten.
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.
dbt is a transformational tool that empowers data teams to quickly build trusted data models, providing a shared language for analysts and engineering teams. Its flexibility and robust feature set make it a popular choice for modern data teams seeking efficiency.
Designed to integrate seamlessly with the data warehouse, dbt enables analytics engineers to transform raw data into reliable datasets for analysis. Its SQL-centric approach reduces the learning curve for users familiar with it,...
I am currently working with Power BI, Tableau, Python, Databricks, Snowflake, and PySpark in the current project. I would rate my overall experience with dbt a nine out of ten.
dbt is easy to use and easy to learn, but it has some limitations that I would love to see mitigated; however, in general, most of my engineers are happy using dbt.My advice for others looking into using dbt is that it is good if you have an organization with engineers who prefer to code and get hands-on, but if you have teams of engineers who prefer a mouse-driven, drag-and-drop type, less technical coding environment, other tools might be more appropriate. I rate dbt overall an eight out of ten.
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.