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[MUSIC]

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In this modern competitive business
environment, the companies that learn how

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to use the mountains of data they've
captured have a competitive advantage.

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Knowledge is power and the databases
are the foundation of that knowledge.

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For the purposes of our SQL courses,

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the databases that we've been using have
been small, with only hundreds of rows.

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In the real world,
databases are very large,

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having millions of rows in a single table.

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These commonly used databases
are called relational databases.

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This term came about from
structuring databases

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in a way that tables are linked to
each other by shared attributes.

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These links are the relationships
between tables.

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As an organization's data needs grow,

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they need a database that can grow and
scale with them.

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How a database schema is designed has
a tremendous impact on the types of

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reports that they can generate and
the performance of that database.

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There are many reasons why relational
databases became the standard for

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application data storage.

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A few of which are eliminating redundant
data reduces storage requirements on disk.

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Well structured and properly segmented
data can be accessed and modified quickly.

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Bad data leads to bad reports.

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Relational databases allow
schema designers to enforce

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good data principles which lead to
better data quality and better reports.

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If you imagine unstructured data in
a poorly designed database schema,

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it might look like this.

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But if you picture organizing your
data with a more thoughtful approach,

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it might start to look like this.

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This is what relational databases do,
they organize data into related tables

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that give context and meaning to
the words and numbers contained within.

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Hi, I'm Andrew,

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a database user, a lifelong learner and
teacher here at Treehouse.

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In this course, we're going to be learning
a lot about relational databases and

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writing complex SQL queries and
joining relational data together.

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In the upcoming videos,

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we'll be taking a look at the concepts
that make relational databases work.

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And start thinking about
data in terms of sets

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as opposed to individual values or rows.