0:00	foreign
0:06	we are going to focus on database
0:09	languages and various database softwares
0:12	at first let's see the various database
0:15	languages talking about these database
0:17	languages these are the exclusive
0:19	languages that directly interact with
0:21	the database so basically these database
0:24	languages are of two types number one
0:26	the data definition language ddl and
0:29	number two the data manipulation
0:32	language DML and in practice they are
0:35	not two separate languages they are
0:37	embedded in a single package only and
0:40	that's why I have mentioned this point
0:41	they are not two separate languages they
0:44	are bundled in the same database
0:46	language package now why do we need
0:48	these two separate languages ddl and DML
0:51	that's what we are going to see in this
0:53	presentation before that let's see one
0:55	of the widely used database languages
0:57	the SQL the structured query language
1:01	with this knowledge let's step into ddl
1:04	the data definition language why do we
1:07	need this data definition language this
1:10	is the language that actually deals with
1:12	the schema of the table what is the
1:14	schema the overall structure of the
1:16	table isn't it see before we insert any
1:19	data into the table say for example we
1:21	want to create a table called employee
1:23	with the columns employee number
1:25	employee name employee date of birth
1:27	employee salary let's take four
1:29	attributes here and if we want to insert
1:32	some data into the table the table
1:34	should exist first right then only we
1:37	will be able to insert or update or
1:39	delete or even select and see what is
1:41	there in the table so before we proceed
1:44	with the data aspects there should exist
1:47	the schema of the table and ddl mainly
1:50	deals with the table the schema
1:53	so ddl stands for data definition
1:55	language and this deals with the
1:58	creation of the table the alteration in
2:00	the table the renaming of a table
2:02	dropping a table or even truncating a
2:05	table what do we mean by this say if we
2:08	want to create a logical structure the
2:10	table structure then creation we need to
2:13	create a table let's assume we have
2:15	created a table and we want to modify
2:17	the schema of the table after creation
2:19
of the table we might be adding a new
2:22
column or dropping a column or even
2:24
changing a data type of the existing
2:26
column so that is also possible using
2:28
ddl so creation of the table also
2:31
alteration of the table then if we want
2:34
to rename the table name again this is
2:36
renaming the schema only so this is also
2:38
ddl and dropping the table means just
2:41
removing the complete information about
2:43
the table even the table itself will be
2:46
dropped from the memory so the complete
2:48
removal of the table structure is
2:50
dropping dropping a table means deleting
2:53
all the data present in the table
2:54
including the structure the schema of
2:57
the table and truncation means it's
2:59
going to delete all the data present in
3:02
the table but the schema Remains the
3:04
structure remains drop deletes
3:06
everything whereas truncate deletes only
3:09
all the data present in the table but
3:11
the table structure exists the schema
3:13
will still persist but it will remove
3:15
all the data present in the table so
3:18
again this is also ddl data definition
3:20
language I hope now you understood why
3:22
do we need two separate languages the
3:25
first language ddl deals with the schema
3:27
and the second language DML is going to
3:29
deal with the data part now what are all
3:32
the additional information that we are
3:33
going to see in ddl actually this ddl is
3:37
used to specify a database schema by a
3:39
set of definitions say if we want to
3:42
create a table or alter or rename or
3:44
drop or trunk it everything is a
3:46
specification of a database schema by a
3:49
set of definitions and that is why we
3:52
call this language as a definition
3:53
language which is data definition
3:55
language ddl and while creating the
3:58
database schema we may include some
4:00
consistency constraints what do we mean
4:03
by consistency constraints let's take it
4:05
is a bank database and there is a column
4:08
in the account table where the balance
4:10
column should not be lesser than or
4:12
equal to 0. in that case we are
4:14
enforcing a constraint to the schema
4:16
that whenever we try to insert a new
4:18
data into the table with the column
4:21
account balance is equal to 0 or lesser
4:24
than 0 the database should not accept
4:26
that because we have enforce a condition
4:29
or a constraint to the table that
4:31
balance column should not be lesser than
4:33
or equal to 0 and this is one of the
4:36
constraints and likewise we can enforce
4:38
a lot of consistency constraints so that
4:41
we can make the database a powerful and
4:43
a consistent one
4:45
so this consistency constraints can be
4:47
enforced on the database in two ways one
4:50
is with the domain constraints and the
4:52
other one is the referential Integrity
4:54
firstly let's focus on the domain
4:56
constraints let's take a table in a
4:59
table we'll be obviously having some
5:00
columns each column is specified by a
5:03
data type this itself is a constraint to
5:05
some extent let's take an example
5:08
employee table the First Column is ID I
5:11
mean employee ID and employee ID is all
5:14
of numbers in that case we are
5:17
specifying the data type to the employee
5:19
ID column as numbers after specifying
5:22
the employee ID column as a number type
5:24
I mean the number data type thereafter
5:27
whenever we try to insert some records
5:29
into the table if the employee ID
5:31
columns is only of numbers only then
5:34
that insertion or updation will be
5:36
accepted otherwise if we try to insert
5:38
some date data type or character data
5:41
type into the employee ID column which
5:43
is set as number type it will not accept
5:45
and this is one of the constraints that
5:48
comes under domain constraints
5:49
specifying a data type itself is a
5:52
domain constraint and also we are
5:54
enforcing some conditions to the columns
5:56
like account balance should not be
5:57
lesser than or equal to zero this is
5:59
also coming under domain constraints
6:01
only and talking about the second one
6:03
the referential Integrity constraint
6:05
suppose we are inserting a value into
6:08
the table and that value should exist in
6:11
other table we are referring the value
6:13
which is inserted in one table and we
6:16
are specifying a condition that that
6:18
value whatever we are going to insert
6:20
into the table that value should exist
6:23
in another table here we are referring
6:25
another table only when this condition
6:27
is satisfied this operation will be
6:30
accepted so this kind of constraint is
6:33
called as referential integrity
6:35
don't worry about this now in the coming
6:37
chapter SQL we are going to focus
6:40
exclusively on all the features of the
6:43
language where we are going to
6:44
exclusively focus on the domain
6:46
constraints and the referential
6:48
Integrity with examples for now just
6:51
understand if it is a domain constraint
6:53
this is restricted to the table it can
6:55
also be a referential Integrity where a
6:58
table is going to refer another table
7:00
basically these two types of constraints
7:02
are special type of constraints that can
7:05
be defined along with the table itself
7:06
but there are situations where we cannot
7:09
express our conditions using domain
7:11
constraints or referential Integrity
7:13
those things can be expressed using
7:15
assertions so assertion in dbms is any
7:18
condition that the data based must
7:21
always satisfy and coming to the next
7:23
point which is authorization this
7:25
authorization simply means that who can
7:28
access what data item generally
7:30
authorization deals with the Privileges
7:32
held by the user who accesses the
7:35
databases authorization can be a read
7:37
authorization insert authorization
7:39
update authorization or delete
7:41
authorization say if a user is having
7:44
read authorization he can read the data
7:46
present in the table but not right if a
7:49
user has insert authorization he will be
7:51
able to insert records into the database
7:54
if he has update authorization he can
7:56
update the database suppose if a user
7:59
wants to delete some data present in the
8:01
database then he should have delete
8:03
authorization so we may assign all or
8:06
none or even any combination of these
8:09
types of authorizations like read insert
8:11
update or delete authorizations and
8:14
coming to the last Point here the data
8:16
dictionary and the metadata what we mean
8:19
by data dictionary generally whatever
8:21
the ddl commands we execute all these
8:24
ddl commands is going to generate an
8:26
output and the output of all the ddl
8:29
command is placed in a special table
8:31
called Data dictionary remember this
8:34
data dictionary is a special type of
8:36
table and what this data dictionary
8:38
table is going to contain it's going to
8:40
contain metadata it means data about
8:43
data so data dictionary is a special
8:46
type of table that can be accessed and
8:48
updated only by the database system and
8:51
not by the regular users of the database
8:53
and that is why I referred this table
8:55
data dictionary as a special type of
8:57
table because it can be accessed and
8:59
updated only by the database system also
9:02
it contains metadata which is data about
9:05
data and whenever any operation is
9:07
carried out on the database the database
9:10
system always consults this table the
9:12
data dictionary before reading or
9:14
updating the data in the database
9:17
we are done with the first language the
9:19
ddl let's now focus on the second one
9:22
the DML we are aware that ddl the data
9:25
definition language deals with the
9:26
schema and this language DML data
9:29
manipulation language which deals with
9:31
the data present in the table say if we
9:33
want to see what are all the data
9:34
present in the table so retrieval is the
9:37
option so retrieval of data or inserting
9:40
data into the database or deleting the
9:42
data from the database or even modifying
9:45
the data from the database all these
9:47
operations are coming under DML the data
9:50
manipulation language remember here only
9:52
data part is dealt and DML does not deal
9:55
with the definition or the schema let's
9:58
assume there is an employee table and we
10:00
want to see all the data present in the
10:01
employee table so we can retrieve the
10:04
data using DML statements and if we want
10:06
to insert a row into the table that is
10:09
also DML only we want to delete or
10:11
modify the existing data this is also
10:14
DML only so in simple terms ddl deals
10:17
with the schema and EML deals with the
10:19
data and basically we have two types of
10:22
DML number one procedural DML and number
10:26
two declarative or non-procedural DML
10:30
procedural DML means we need to specify
10:33
what data is required and how to
10:36
retrieve those data whereas in
10:38
non-procedural we are simply going to
10:40
specify what data is required and how we
10:43
are going to retrieve the data we need
10:45
not specify that anywhere in the coming
10:47
lectures we are going to focus on
10:49
procedural DML and non-procedural DML
10:52
elaborately if we write a statement
10:54
requesting the retrieval of information
10:56
we call that statement as a query so if
10:59
we write a DML statement that is
11:01
requesting the retrieval of the
11:03
information from the database then that
11:05
statement is referred as a query and
11:07
generally the query language and DML are
11:11
used synonymously so before we sign out
11:14
let's see various dbms softwares
11:16
basically a lot of softwares that are
11:19	available for dbms the first software is
11:21	Oracle then MySQL IBM db2 Microsoft SQL
11:26	Server post gray SQL or simply post gray
11:30	SQL Razer SQL info mix mongodb redis
11:36	teradata elasticsearch Amazon RDS
11:40	Microsoft Access
11:42	sqlite ulti bass and improvado so these
11:46	are all the example softwares that are
11:48	available for dbms so what we have seen
11:51	today the dbms language is ddl and DML
11:54	and also we have seen few database
11:56	softwares and that's it guys I hope you
11:59	guys enjoyed this presentation and thank
12:01	you for watching
12:03	[Music]
12:03	[Applause]
12:12	thank you