This story delves into advanced SQL techniques that can be useful for data science practitioners. On this piece, I’ll provide an in depth exploration of expert-grade SQL queries I take advantage of each day in my analytics projects. SQL, together with modern data warehouses, forms the backbone of knowledge science. It’s an indispensable tool for data manipulation and user behaviour analytics. The techniques I’m going to discuss are designed to be practical and useful from the information science perspective. Mastery of SQL is a worthwhile skill, crucial for a big selection of projects, and these techniques have significantly streamlined my each day work. I hope it is going to be useful for you as well.
On condition that SQL is the first language utilized by data warehouse and business intelligence professionals, it’s an excellent alternative for sharing data across data platforms. Its robust features facilitate seamless data modelling and visualization. It stays the preferred technique of communication for any data team and nearly every data platform available out there.
We are going to use BigQuery’s standard SQL dialect. It’s free and simple to run the queries I wrote and provided below.
