All language subtitles for [SubtitleTools.com] What Is A Database- - Learning Oracle 12c [Video]

In this lesson, we'll
examine the question,

what is a database?

Let's imagine for
a moment that we're

in a room with a telephone
book for the 50 largest

American cities.

I tell you to find
the phone number

of Carl Roth in Los Angeles.

What would you do?

Simply pick up the Los
Angeles telephone book,

flip to the R's, and
find his number--

not terribly difficult.

But what if, first, I tore out
all the pages of each book,

threw the pages in the air, and
scattered them on the floor?

Then I asked you to find
Carl Roth in Los Angeles.

That task is considerably
more difficult.

This is a good example of why
the database is so important.

Think about all the
information about you

that exist in databases--

hobbies, our preferences,
our interest,

purchases that we've made,
friends that we have.

All of this information
must be stored somewhere.

And the vast majority of
it is stored in databases.

Put simply, a database is an
organized collection of data.

Computers use databases
to organize and store

that data in a way that it
can be easily retrieved.

But the kind of
databases we have today

haven't always
been in existence.

The first computers were
primarily used for computation

in scientific research and
even some military applications

to calculate numbers quickly.

As time went on, businesses
began to use them, as well.

When they came into
more common use,

requirements increased
to be able to store

much of the data that
was being calculated.

As more data was
stored, new ways

were required to preserve and
retrieve that data quickly.

The first databases were
called flat-file databases.

A flat-file database
is something

that we're basically
familiar with.

If you've ever seen a
comma-separated values

file, or CSV,
you've seen the way

a flat-file database is stored.

Let's look at an example of
some simple flat-file values.

Here we see first
name, last name,

and other information about
our customers in the database.

Notice that the first
value in each row

is the first name and the
second value in each row

is the last name.

This is consistent
across all of the values.

The data is read from,
essentially, left to right.

The first value is read,
than a comma delimiter,

the second value is read,
and so on and so forth.

Each individual value within
that row, separated by commas,

is called a field.

This data was generally accessed
using programmatic methods

that read individual records.

This example of a
flat-file database

is very limited in that there's
only a few records and fields.

In a real flat-file
database, there

could be millions and millions
of records and hundreds

of fields.

This is one of the problems
that developed over time.

The flat files
grew unmanageable.

Another approach
was needed to be

able to manage
this type of data.

That's where a man named Dr.
Ted Codd comes into the story.

Dr. Codd, employed
at IBM at the time,

was working on a solution
for some of these problems.

In the 1970s, Dr.
Codd presented a paper

that introduced a new
type of storage paradigm

for databases, called
the relational paradigm.

The relational
paradigm was a way

to deal with many
of the problems

in typical flat-file databases.

The relational paradigm depends
on organizing information

into what's called
entities and attributes.

An entity is any
person, place, or thing.

Attributes are things about
that person, place, or thing.

So we might organize
our information the way

you see here.

We have an employee entity
that has attributes,

such as first name
and last name.

Thus, we can organize
all of the information

that we've had in
flat-file databases

and put it into an entity
attribute structure.

The real strength of Dr.
Codd's relational model

is that the information can be
related to other information.

That is to say, we can
relate one entity to another.

In a flat-file database
all the information

about a given employee
would basically

be in a single record.

In Dr. Codd's model, we
separate that information out

and relate it.

Here we have
employee information

and address information.

Dr. Codd's theory was that
similar pieces of information

could be structured
in such a way

that they formed relationships.

So rather than combining
numerous pieces of information

together in the same
structure, we instead

separate them out into
related pieces of information.

Because both of these
entities share a common piece

of information, in
this case employee ID,

they can be related.

This type of database is known
as an RDBMS or Relational

Database Management System.

So why is this model better?

The primary reason
we use an RDBMS

is the removal of
duplicate data.

Consider an order entry
system with customer records.

If an individual
places numerous orders,

the customer's
basic information,

such as name and
contact information,

must be stored in every record
using the flat-file method.

With the relational
method, we simply

have an entity for
customer information

and an other entity
for order information.

We then relate them together.

The process of transforming
a flat-file data

model into a relational one
is known as normalization.

Today, we refer to an entity as
a table and records and fields

as rows and columns,
respectively.

The RDBMS has been the data
storage model of choice

for three decades, now.

And although Oracle is the RDBMS
with the largest market share,

there are other popular
systems, as well.

IBM's flagship database
product is known as Db2.

It evolved from their
first RDBMS product,

called System R. It is very
popular with customers that

use IBM hardware and
includes the ability

to run on mainframe systems.

Oracle actually has another
RDBMS that it provides,

although it is free of
licensing restrictions.

When Oracle acquired
Sun Microsystems,

they also acquired
the MySQL RDBMS

and continue to
support it today.

SQL Server from Microsoft
is another popular RDBMS.

Microsoft began
work on SQL Server

when they purchased the code
base for Sybase SQL Server

from Sybase.

Although popular
on Windows systems,

SQL Server lacks the
cross-platform abilities

of other database systems since
it cannot run on any other

operating system
besides Windows.