I am not very familiar with dbt's version control system. I cannot identify any improvements in dbt because I am still exploring more functionality. I have been working with dbt for only three years, so I am exploring more functionalities and cannot see any limitations or improvement areas at this time. In the past, I used the seed functionality, which is used to load raw files, individual files, or static files into the database. Going forward, if dbt can improve or implement more features on the seed side, that would be beneficial, especially when we have large files available that take time to load the data into Snowflake database.
dbt can be improved as I find the co-pilot in dbt is not very good, and my team has tried using it but opted to move off it and use other co-pilots such as GitHub. Additionally, the debugging capabilities in dbt are practically nonexistent, making it very hard to troubleshoot and debug if you write incorrect Jinja code.dbt is not as stable as I would prefer, as there have been a few outages this year.
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.
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 not very familiar with dbt's version control system. I cannot identify any improvements in dbt because I am still exploring more functionality. I have been working with dbt for only three years, so I am exploring more functionalities and cannot see any limitations or improvement areas at this time. In the past, I used the seed functionality, which is used to load raw files, individual files, or static files into the database. Going forward, if dbt can improve or implement more features on the seed side, that would be beneficial, especially when we have large files available that take time to load the data into Snowflake database.
dbt can be improved as I find the co-pilot in dbt is not very good, and my team has tried using it but opted to move off it and use other co-pilots such as GitHub. Additionally, the debugging capabilities in dbt are practically nonexistent, making it very hard to troubleshoot and debug if you write incorrect Jinja code.dbt is not as stable as I would prefer, as there have been a few outages this year.
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.