The ability to code up SQL is necessary to landing and succeeding in any data science role. I’ve got four principles that will help you succeed in all your SQL: Before You Write Any Code, Determine the Right Grain; Formatting Matters; Use CTEs, not Subqueries; and Tell a Story with Code Comments
Tips for improving your data science skillset
It goes without saying that the ability to code up SQL is necessary to landing and succeeding in any data science role. There isn’t any evidence that this is changing anytime soon, SQL is here to stay, so mastering this skill is an unequivocally worthwhile investment. Whether you’re looking for your first role in data science, brushing up on your SQL skills for your next round in the job market, or looking to level up your career I’ve got four principles that will help you succeed in all your SQL-related endeavors.
Let’s dive right in.
SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
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