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[music] In this video, we'll take a high-level look
at SQL.

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SQL is a bit different from the other languages
we’ve covered so far.

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First off, it's formally pronounced “ess
cue el,” although some people say “sequel.”

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While the acronym stands for “Structured
Query Language,” many people do not consider

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SQL to be like other software development
languages because it's a non-procedural language

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and its scope is limited to querying and managing
data.

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While it is not a “data science” language
per se, data scientists regularly use it because

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it's simple and powerful!

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Another couple of neat facts about SQL: it's
much older than Python and R, by about 20

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years, having first appeared in 1974.

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And, SQL was developed at IBM!

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This language is useful in handling structured
data; that is, the data incorporating relations

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among entities and variables.

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SQL was designed for managing data in relational
databases.

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Here you can see a diagram showing the general
structure of a relational database.

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A relational database is formed by collections
of two-dimensional tables; for example, datasets

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and Microsoft Excel spreadsheets.

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Each of these tables is then formed by a fixed
number of columns and any number of rows.

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BUT!

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Even though SQL was originally developed for
use with relational databases, because it's

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so pervasive and easy to use, SQL interfaces
for many NoSQL and big data repositories have

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also been developed.

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The SQL language is subdivided into several
language elements, including clauses, expressions,

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predicates, queries, and statements.

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So what makes SQL great?

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Knowing SQL will help you do many different
jobs in data science, including business and

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data analyst, and it's a must in data engineering.

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When performing operations with SQL, you access
the data directly.

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There's no need to copy it beforehand.

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This can speed up workflow executions considerably.

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SQL is the interpreter between you and the
database.

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SQL is an American National Standards Institute,
or "ANSI," standard, which means if you learn

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SQL and use it with one database, you will
be able to easily apply that SQL knowledge

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to many other databases.

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There are many different SQL databases available,
including MySQL, IBM Db2, PostgreSQL, Apache

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OpenOffice Base, SQLite, Oracle, MariaDB,
Microsoft SQL Server, and more.

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The syntax of the SQL you write might change
a little bit based on the relational database

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management system you’re using.

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If you are looking to learn SQL you would
be best served to focus on a specific relational

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database and then plug into the community
for that specific platform.

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There are also many great introductory courses
on SQL available!