[music] In this video, we'll take a high-level look at SQL.
SQL is a bit different from the other languages we’ve covered so far.
First off, it's formally pronounced “ess cue el,” although some people say “sequel.”
While the acronym stands for “Structured Query Language,” many people do not consider
SQL to be like other software development languages because it's a non-procedural language
and its scope is limited to querying and managing data.
While it is not a “data science” language per se, data scientists regularly use it because
it's simple and powerful!
Another couple of neat facts about SQL: it's much older than Python and R, by about 20
years, having first appeared in 1974.
And, SQL was developed at IBM!
This language is useful in handling structured data; that is, the data incorporating relations
among entities and variables.
SQL was designed for managing data in relational databases.
Here you can see a diagram showing the general structure of a relational database.
A relational database is formed by collections of two-dimensional tables; for example, datasets
and Microsoft Excel spreadsheets.
Each of these tables is then formed by a fixed number of columns and any number of rows.
BUT!
Even though SQL was originally developed for use with relational databases, because it's
so pervasive and easy to use, SQL interfaces for many NoSQL and big data repositories have
also been developed.
The SQL language is subdivided into several language elements, including clauses, expressions,
predicates, queries, and statements.
So what makes SQL great?
Knowing SQL will help you do many different jobs in data science, including business and
data analyst, and it's a must in data engineering.
When performing operations with SQL, you access the data directly.
There's no need to copy it beforehand.
This can speed up workflow executions considerably.
SQL is the interpreter between you and the database.
SQL is an American National Standards Institute, or "ANSI," standard, which means if you learn
SQL and use it with one database, you will be able to easily apply that SQL knowledge
to many other databases.
There are many different SQL databases available, including MySQL, IBM Db2, PostgreSQL, Apache
OpenOffice Base, SQLite, Oracle, MariaDB, Microsoft SQL Server, and more.
The syntax of the SQL you write might change a little bit based on the relational database
management system you’re using.
If you are looking to learn SQL you would be best served to focus on a specific relational
database and then plug into the community for that specific platform.
There are also many great introductory courses on SQL available!