0:06	hello everyone welcome back in this
0:08	presentation let's focus on the
0:10	introduction to data models
0:13	let's directly step into the topic of
0:15	today the data models what do we mean by
0:18	this data model this data model is
0:20	actually the underlying structure of a
0:22	database what do we mean by this
0:25	actually this data model is a conceptual
0:27	tool that describes the data the
0:30	relationship among the data the data
0:32	semantics and the constraints what do we
0:35	mean by this see we know basically a
0:37	database is actually a collection of
0:39	interrelated data when we say that it is
0:42	going to be the collection of
0:43	interrelated data we know basically this
0:46	is going to store the data it's going to
0:48	store the interrelated data i mean the
0:50	relationship among the data is also
0:52	existing we also need to deal with the
0:55	data semantics and the constraints i
0:58	mean what kind of data are stored what
1:00	kind of data are not permitted all these
1:02	things so we obviously need data models
1:05	in order to deal with the databases so
1:08	this data model is actually acting as a
1:10	conceptual tool that describes the data
1:13	the data relationship the data semantics
1:16	and the data constraints so obviously we
1:18	need to design the database at physical
1:21	level logical level and the view level
1:24	we know databases uses three tier
1:26	architecture so we need to design or we
1:28	need to look into the database in the
1:30	design perspective at three levels one
1:33	the physical level two the logical level
1:36	three the final one is the view level we
1:39	are done with the basics of data model
1:41	let's now see the various categories of
1:44	data model in this presentation we are
1:46	going to focus on four different
1:47	categories of data model the first one
1:50	is the relational model the second one
1:53	is the entity relationship model the
1:55	third one is the object-based data model
1:58	and the last one is the semi-structured
2:00	data model of course we have other data
2:02	models as well but in this presentation
2:04	we are going to focus only on these four
2:06	data models let's start with the first
2:08	data model the relational model
2:11	basically a database is a collection of
2:13	tables and we know this table is going
2:16	to collect or store the data and these
2:18	tables are also going to establish or
2:21	maintain the relationship among the
2:23	tables so what do we mean by this see we
2:25	are going to store the data in databases
2:28	where databases are collection of tables
2:30	and these tables are going to store the
2:32	data in the form of rows and columns
2:34	let's say we have two tables one is the
2:36	student table other one is the
2:38	instructor table and this student table
2:40	is going to contain the information
2:42	about the student and obviously the
2:44	instructor table is going to store the
2:46	data about the instructors now obviously
2:48	student and instructor are somehow
2:50	related isn't it the relationship is
2:53	also a table in this case so in
2:55	relational model everything is of tables
2:58	the data are obviously going to be
2:59	stored in the table and the relationship
3:02
are also represented in the form of
3:04
tables no worries when we see some
3:05
examples you will be able to understand
3:07
things so in relational model everything
3:10
is represented in the form of tables and
3:13
we know basically a table is going to
3:15
contain multiple columns and each column
3:18
in the table will have unique names
3:20
likewise in a database we may have
3:22
multiple tables and each table will have
3:24
unique names so in relational model we
3:27
have multiple columns in the table with
3:28
the unique names and we may also have
3:30
multiple tables with a unique name in a
3:33
database now why it is named as a
3:35
relational model because in rtbms the
3:38
relational database management system we
3:40
refer tables as relations because in
3:44
relational model everything is of
3:46
relation obviously the data are going to
3:48
be stored in the relation or table only
3:50
and the relationship among the data or
3:52
the relationship among the table is also
3:54
going to be stored in a relation only
3:57
and this relational model is also
3:58
referred as a record-based model and
4:01
what is a record it is actually a fixed
4:04
format records of several types of
4:06
several data types i will explain about
4:08
this when we see an example so in simple
4:11
terms relational model is also referred
4:14
as a record-based model and what is a
4:16
record actually each record defines a
4:19
fixed number of fields or attributes say
4:22
if we say something as a record each
4:24
record is going to have a fixed number
4:27
of fields or attributes don't worry
4:29
about this now in the next slide we are
4:31
going to see some examples now is this
4:33
model widely used yes this relational
4:37
model is the most widely used data model
4:40
in this contemporary world so when i say
4:42
this is the most widely used data model
4:45
obviously the current database systems
4:47
are based on the relational model only
4:49
so we are done with the basics of
4:51
relational model before we step into the
4:53
next data model let's see an example
4:58
let's say this is the relational
5:00
database management system or simply
5:02
rdbms where this database management
5:05
system is a collection of databases and
5:07
we know databases are actually
5:09
collection of tables and we know a table
5:12
is a collection of various fields and
5:14
the collection of various fields are
5:16
referred as the record say if we talk
5:18
about an employee relation or an
5:21
employee table let's say this employee
5:23
table contains four attributes or four
5:25
columns first name last name salary and
5:28
department number and this particular
5:31
relation has four columns or four
5:33
attributes the first name last name
5:36
salary and department number can you see
5:39
here tom 4 30 0003 this complete
5:44
information are referred as a record
5:46
where this record is actually having
5:48
four fields the first name field the
5:50
last name field salary and department
5:53
number fields so in simple terms a
5:55
record is a collection of fields and
5:58
collection of fields are referred as a
5:59
table and collection of tables are
6:01
referred as database and collection of
6:04
databases are referred as the relational
6:06
database management system so in simple
6:09
terms in relational database system
6:11
multiple relations are there each
6:13
relation is actually a table and each
6:15
table will contain multiple fields and
6:18
the collection of fields are referred as
6:20
records
6:21
we also see a diagram here don't worry
6:23
about this now in the next data model we
6:25
will see about this
6:27
so we are done with the first data model
6:29
the relational data model let's now move
6:32
on to the next data model the er model
6:35
the entity relationship model so this
6:38
entity relationship model is also
6:40
referred as the er data model or simply
6:42
er model so e stands for entity r stands
6:46
for relationship what do we mean by this
6:48
entity we know basically this er model
6:51
is actually a collection of basic
6:53
objects and these objects are referred
6:56
as entities and when we say this is a
6:58
collection of multiple entities and
7:00
obviously there will be relationship
7:02
among entities right so there will be a
7:04
relationship among student entity as
7:06
well as instructor entity and when we
7:09
say this entity is a collection of basic
7:11
objects these objects are real-world
7:14
entities or real-world things right so
7:16
we can say an entity is a real world
7:19
thing or object and when we say that
7:21
this entity is a real world thing or
7:23
object obviously each entity or each
7:26
object is distinguishable from other
7:29
objects now is this er model is widely
7:32
used yes like relational model er model
7:35
is also widely used but the important
7:37
thing to note here about er model is
7:40
this er model is widely used in the
7:42
database design before you start
7:45
creating the database before you start
7:47
creating the table we are going to use
7:49
the er model in order to design the
7:51
database in the previous data model i
7:54
mean the relational model the current
7:56
database systems are actually using the
7:57
relational model whereas here the second
8:00
data model which is the er model we are
8:02
going to use this er model for designing
8:05
the database
8:06
let's see an example then it will be
8:08
easy for you to understand here is the
8:10
example of an er model can you see here
8:13
everything is referred as an entity this
8:15
employee is an entity dependent is an
8:17
entity project department are entities
8:21
and each entity or each object is
8:23
described by some attributes salary ssn
8:27
name gender or sex and name attribute
8:30
has three more sub attributes the first
8:32
name middle name and the last name so
8:34
don't worry about this er model now
8:37
anyway in the next chapter we are going
8:39
to exclusively focus on the database
8:41
design aspects where we are going to see
8:43
about the er model we are going to see
8:45
various examples about er model so for
8:48
now just understand this er model is a
8:50
schematic or diagrammatic representation
8:53
so that this can be used for designing
8:55
the database and also please be noted
8:58
here that this entity is related to
9:01
other entity through some relationships
9:03
can you see here this employee entity
9:05
has some relationship with other
9:07
entities like department and project and
9:10
what is the name of the relationship
9:12
this employee works for department this
9:14
works for is a relationship this manages
9:17
is a relationship works on is also a
9:19
relationship so this is an entity these
9:22
are all attributes and these are all the
9:24
relationship no worries about the
9:26
terminologies used we are going to
9:28
exclusively focus on the database design
9:31
aspects in the next chapter so we are
9:33
done with the second data model the
9:35
entity relationship model let's now move
9:37
on to the third data model the object
9:39
based model we know object oriented
9:41
languages like the c plus plus java c
9:45
ash or c sharp we know these are all the
9:47
object oriented programming languages
9:50
suppose if our front end is designed
9:52
using object oriented programming
9:53
language we need to have the backend
9:56
which also supports the front end right
9:58
so in that case we are in a need for
10:00
object oriented data model and that is
10:03
why we are ending up here with the
10:04
object-based model where this
10:06
object-based model is actually using the
10:09
er model with the object-oriented
10:11
features in the previous data model we
10:13
have seen about the entity relationship
10:15
model where we have seen everything is
10:17
of entities where each entities are
10:19
referred as an object which are real
10:21
world entities or real-world things
10:24
and each real-world entity the objects
10:26
are distinguishable from other objects
10:28
so what we are going to do here is in
10:30
the object-based model we are going to
10:32
make use of the features of the er model
10:35
along with the object oriented features
10:37
like data encapsulation inheritance etc
10:41
we also have a variation of the
10:43
object-based data model which is object
10:46
relational data model where this object
10:48
relational data model which is the
10:50
combination of object-based model which
10:52
is this along with the relational model
10:55
which is the first data model we have
10:56
seen object-based model when it is
10:59
combined with the relational model we
11:01
get object relational data model
11:03
before we step into the fourth data
11:05
model let's see the example so in this
11:07
example we can see that this is an
11:10
object person is an object which
11:12
contains attributes like name age
11:14
address and phone number so this can
11:17
also be represented as an er
11:18
representation this is an entity or an
11:21
object person which contains attributes
11:23
like name
11:25
age address and phone number so don't
11:27
worry about this now when the course
11:29
progresses we will be able to understand
11:31
things clearly so we are done with the
11:34
third data model the object-based model
11:37
let's see the last data model the
11:39
semi-structured data model the name
11:41
itself says that this data model is
11:44
already semi-structured
11:46
it means it's going to deal with the
11:48
specification of the data what do we
11:50
mean by this it means the individual
11:53
data items of the same type may have
11:56
different sets of attributes what do we
11:58
mean by this this data model is mainly
12:01
used for transferring the data among
12:03
applications so if there are two
12:05
different applications and data transfer
12:07
needs to be done obviously data needs to
12:09
be stored somewhere right in the
12:11
database if we use semi-structured data
12:14
model then transferring the data among
12:16
applications is also easier no worries
12:19
in the last phase of this subject we are
12:21
going to exclusively focus on a special
12:23
language the extensible markup language
12:26
where we will be understanding clearly
12:27
about this semi-structured data model so
12:30
for now just understand two different
12:33
applications need to communicate with
12:35
each other and if they want to use the
12:37
databases then we can go for
12:39
semi-structured data model where it
12:41
deals with the specification of data and
12:44
we can clearly witness that this is
12:46
contrast to the previous data models we
12:49
have seen i mean this is contrast to the
12:51
previous models like the relational
12:52
model the entity relationship model or
12:55
simply er model and the object-based
12:57
model
12:58
and the language that supports the
13:00
semi-structured data model is the
13:01
extensible markup language simply xml
13:05
before we see the other data models
13:07
let's see an example for xml say here i
13:10
am going to create a note where this
13:13
note is from neso academy to all
13:15
students and the subject of this note is
13:18
thank you and the body of this note is
13:20
thank you for subscribing neso academy
13:22
good luck and this body ends here and
13:25
this is the end of the note can you see
13:27
here this is like the html language but
13:30
the difference here in html we have
13:32
predefined tags here we can create our
13:35
own tags can you see here this is a note
13:38
where i am creating my own tag this is a
13:40
note this note has a from field or a
13:43
from tag so this from is a user defined
13:46
tag these two subject body and note all
13:49
are user-defined tag can you see here
13:51
the hierarchy or even the structure here
13:54
this note is the parent element and this
13:57
contains sub elements like from to
13:59
subject body and this is the end of this
14:02
note tag i know things will be unclear
14:04
at the moment but for now just
14:06
understand the structure this contains
14:08
the data which is naso academy all
14:11
students thank you thank you for
14:13
subscribing neso academy good luck all
14:15
these are the data that we are going to
14:17
store or transfer at the same time these
14:20
data are also structured and this is how
14:23
it is structured the node is the outer
14:25
element or the parent tag which contains
14:27
sub tags like from to subject body and
14:31
each data has its own structure this
14:33
data belongs to this from and this data
14:36
is belonging to two and this is how data
14:39
is actually structured and stored and
14:41
that's why we call xml is a
14:43
semi-structured language
14:45
and this is what the point two of the
14:47
semi-structured data model which we have
14:49
seen in the previous slide says
14:51
we can have multiple nodes with multiple
14:53
different elements in this node we have
14:56
from to subject and body we may have
14:58
other nodes with all these four elements
15:01
or without all these four elements or
15:03
with addition of other elements or tags
15:06
so we are done with the fourth data
15:07
model the semi-structured data model
15:10
before we sign out let's see other data
15:12
models anyway i'm not going to focus
15:14
more on these data models because most
15:16
of these models are obsolete now the
15:18
first thing is the network data model
15:20
and the hierarchical data model nowadays
15:23
we are not using this because these
15:25
models are tied closely to the
15:27
underlying implementation if any data
15:29
model is tied closely to the underlying
15:31
implementation obviously it is
15:33
complicating the task of modeling the
15:36
data and these models are not used
15:38
nowadays except we have these models in
15:41
the old databases so these data models
15:44
like the network data model and
15:45
hierarchical data model are going to use
15:48
structures like the trees or graphs
15:51
and that's it guys in this presentation
15:53
we have seen about the data models and
15:55
the various data models like the
15:57	relational data model the entity
15:59	relationship or simply er data model
16:01	
object-based data model and
16:03	semi-structured data model we also have
16:05	seen other data models that are not
16:07	widely used nowadays i hope the session
16:09	is informative and thank you for
16:11	watching
16:12	[Music]
16:13	[Applause]
16:15	[Music]
16:23	you