Although this is not directly related to machine learning/deep learning but a data warehouse is something that data scientists have to deal with while building machine learning models. I hope it would be somewhat useful for people to know an engineering/business/data science perspective for choosing a data warehouse.
We recently selected a data warehouse after making some basic data for some data warehouses: AWS Redshift, AWS Athena, Snowflake, Google BigQuery. In this slide, I share some aspects of our business that led us to choose Snowflake and what were the pros and cons of different actions.
It mainly consists of exchanging POC experiences in different data warehouses. One thing that is missing from the slides is BigQuery. I recently got certified Google Certified Professional - Data Engineer. so I already knew his skills, so I did not do POC. Our technology was far superior to AWS, so switching to GCP would make sense if there were significant advantages you could not see in comparison when choosing a data warehouse.
I make the next post so I can share the good pieces of snowflakes in the coming weeks. If in doubt, add some comments and I will try to contact you as soon as I arrive.
Thanks and Regards,