SQL Query V.S. Data Transforms

I am currently building a Type 2 dimension prototype for our datamart on Snowflake and being from a SSIS background, I am used to having a SQL query as the source of the data flow. I know Matillion provides many transforms to accomplish the same goal as a SQL query (join, aggregate, ...) but it seems so much easier to simply hand-write the equivalent query and use the SQL component as the source in a transformation job.

 

I would like to have your thoughts on this, is there a downside to using a SQL query instead of the Matillion transforms ? What is your experience on this ?

 

Chris

@callaire-c​ - as you rightly mentioned, hand-coding a SQL query would be easier if you are migrating from an existing platform.

But by leveraging the Matillion transformation components you are future proofing your data pipeline

  • by making it easier to modify / make changes
  • improving explainability for new and junior data engineers
  • simplify troubleshooting and data lineage questions.
  • iteratively build your data pipeline by running each step and checking results.

I had similar apprehensions but once you start using the low-code methodology of building transformations, you would not want to hand-code your SQL queries.

Hope this helps.