The document discusses various forms of database normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), and fourth normal form (4NF). It provides examples of database schemas that are and are not in each normal form and describes how to decompose schemas into normal form through lossless normalization techniques.

1. Structured Query Language
Course:-MCA-II
Subject:-Database Management System
Unit:-4

2.  This is the process which allows you to winnow out
redundant data within your database.
 This involves restructuring the tables to successively
meeting higher forms of Normalization.
 A properly normalized database should have the
following characteristics
 Scalar values in each fields
 Absence of redundancy.
 Minimal use of null values.
 Minimal loss of information.
Definition

3.  Levels of normalization based on the amount of
redundancy in the database.
 Various levels of normalization are:
 First Normal Form (1NF)
 Second Normal Form (2NF)
 Third Normal Form (3NF)
 Boyce-Codd Normal Form (BCNF)
 Fourth Normal Form (4NF)
 Fifth Normal Form (5NF)
 Domain Key Normal Form (DKNF)
Levels of Normalization
Redundancy
NumberofTables
 Most databases should be 3NF or BCNF in order to avoid
the database anomalies.
 Most databases should be 3NF or BCNF in order to avoid
the database anomalies.
Complexity

4. Levels of Normalization
Each higher level is a subset of the lower level
DKNF
1NF
2NF
3NF
4NF
5NF

5. A table is considered to be in 1NF if all the fields contain
only scalar values (as opposed to list of values).
Example (Not 1NF)
First Normal Form (1NF)
Author and AuPhone columns are not scalarAuthor and AuPhone columns are not scalar
0-321-32132-1 Balloon Sleepy,
Snoopy,
Grumpy
321-321-1111,
232-234-1234,
665-235-6532
Small House 714-000-0000 $34.00
0-55-123456-9 Main Street Jones,
Smith
123-333-3333,
654-223-3455
Small House 714-000-0000 $22.95
0-123-45678-0 Ulysses Joyce 666-666-6666 Alpha Press 999-999-9999 $34.00
1-22-233700-0 Visual
Basic
Roman 444-444-4444 Big House 123-456-7890 $25.00
ISBN Title AuName AuPhone PubName PubPhone Price

6. 1. Place all items that appear in the repeating group in a new table
2. Designate a primary key for each new table produced.
3. Duplicate in the new table the primary key of the table from
which the repeating group was extracted or vice versa.
Example (1NF)
1NF - Decomposition
0-321-32132-1 Balloon Small House 714-000-0000 $34.00
0-55-123456-9 Main Street Small House 714-000-0000 $22.95
0-123-45678-0 Ulysses Alpha Press 999-999-9999 $34.00
1-22-233700-0 Visual
Basic
Big House 123-456-7890 $25.00
ISBN Title PubName PubPhone Price
ISBN AuName AuPhone
0-123-45678-0 Joyce 666-666-6666
1-22-233700-0 Roman 444-444-4444
0-55-123456-9 Smith 654-223-3455
0-55-123456-9 Jones 123-333-3333
0-321-32132-1 Grumpy 665-235-6532
0-321-32132-1 Snoopy 232-234-1234
0-321-32132-1 Sleepy 321-321-1111

7. 1. If one set of attributes in a table determines
another set of attributes in the table, then the
second set of attributes is said to be functionally
dependent on the first set of attributes.
Example 1
Functional Dependencies
0-321-32132-1 Balloon $34.00
0-55-123456-9 Main Street $22.95
0-123-45678-0 Ulysses $34.00
1-22-233700-0 Visual
Basic
$25.00
ISBN Title Price Table Scheme: {ISBN, Title, Price}
Functional Dependencies: {ISBN} 
{Title}
{ISBN} 
{Price}

8. Example 2
Functional Dependencies
1 Big House 999-999-9999
2 Small House 123-456-7890
3 Alpha Press 111-111-1111
PubID PubName PubPhone Table Scheme: {PubID, PubName, PubPhone}
Functional Dependencies: {PubId}  {PubPhone}
{PubId}  {PubName}
{PubName, PubPhone}  {PubID}
AuID AuName AuPhone
6 Joyce 666-666-6666
7 Roman 444-444-4444
5 Smith 654-223-3455
4 Jones 123-333-3333
3 Grumpy 665-235-6532
2 Snoopy 232-234-1234
1 Sleepy 321-321-1111
Example 3
Table Scheme: {AuID, AuName,
AuPhone}
Functional Dependencies: {AuId} 
{AuPhone}
{AuId} 
{AuName}
{AuName, AuPhone}  {AuID}

9. FD – Example
 Database to track reviews of papers submitted to an academic
conference. Prospective authors submit papers for review and
possible acceptance in the published conference proceedings.
Details of the entities
 Author information includes a unique author number, a
name, a mailing address, and a unique (optional) email
address.
 Paper information includes the primary author, the paper
number, the title, the abstract, and review status (pending,
accepted, rejected)
 Reviewer information includes the reviewer number, the
name, the mailing address, and a unique (optional) email
address

10. FD – Example
 Functional Dependencies
 AuthNo  AuthName, AuthEmail, AuthAddress
 AuthEmail  AuthNo
 PaperNo  Primary-AuthNo, Title, Abstract,
Status
 RevNo  RevName, RevEmail, RevAddress
 RevEmail  RevNo
 RevNo, PaperNo  AuthComm, Prog-Comm,
Date, Rating1, Rating2, Rating3, Rating4,
Rating5

11.  For a table to be in 2NF, there are two requirements
 The database is in first normal form
 All nonkey attributes in the table must be functionally
dependent on the entire primary key
 Example 1 (Not 2NF)
 Scheme  {Title, PubId, AuId, Price, AuAddress}
 Key  {Title, PubId, AuId}
 {Title, PubId, AuID}  {Price}
 {AuID}  {AuAddress}
 AuAddress does not belong to a key
 AuAddress functionally depends on AuId which is a
subset of a key
Second Normal Form (2NF)

12. Example 2 (Not 2NF)
Scheme  {City, Street, HouseNumber, HouseColor, CityPopulation}
1. key  {City, Street, HouseNumber}
2. {City, Street, HouseNumber}  {HouseColor}
3. {City}  {CityPopulation}
4. CityPopulation does not belong to any key.
5. CityPopulation is functionally dependent on the City which is
a proper subset of the key
Example 3 (Not 2NF)
Scheme  {studio, movie, budget, studio_city}
1. Key  {studio, movie}
2. {studio, movie}  {budget}
3. {studio}  {studio_city}
4. studio_city is not a part of a key
5. studio_city functionally depends on studio which is a proper
subset of the key
Second Normal Form (2NF)

13.  If a data item is fully functionally dependent on only a part
of the primary key, move that data item and that part of the
primary key to a new table.
 If other data items are functionally dependent on the same
part of the key, place them in the new table also
 Make the partial primary key copied from the original table
the primary key for the new table. Place all items that appear
in the repeating group in a new table
 Example 1 (Convert to 2NF)
 Old Scheme  {Title, PubId, AuId, Price,
AuAddress}
 New Scheme  {Title, PubId, AuId, Price}
 New Scheme  {AuId, AuAddress}
2NF - Decomposition

14.  This form dictates that all non-key attributes of a table must be
functionally dependent on a candidate key i.e. there can be no
interdependencies among non-key attributes.
 For a table to be in 3NF, there are two requirements
 The table should be second normal form
 No attribute is transitively dependent on the primary key
 Example (Not in 3NF)
 Scheme  {Title, PubID, PageCount, Price }
 Key  {Title, PubId}
 {Title, PubId}  {PageCount}
 {PageCount}  {Price}
 Both Price and PageCount depend on a key hence 2NF
 Transitively {Title, PubID}  {Price} hence not in 3NF
Third Normal Form (3NF)

15. Example 2 (Convert to 2NF)
Old Scheme  {Studio, Movie, Budget, StudioCity}
New Scheme  {Movie, Studio, Budget}
New Scheme  {Studio, City}
Example 3 (Convert to 2NF)
Old Scheme  {City, Street, HouseNumber, HouseColor,
CityPopulation}
New Scheme  {City, Street, HouseNumber, HouseColor}
New Scheme  {City, CityPopulation}
2NF - Decomposition

16. Example 2 (Not in 3NF)
Scheme  {Studio, StudioCity, CityTemp}
1. Primary Key  {Studio}
2. {Studio}  {StudioCity}
3. {StudioCity}  {CityTemp}
4. {Studio}  {CityTemp}
5. Both StudioCity and CityTemp depend on the entire key hence 2NF
6. CityTemp transitively depends on Studio hence violates 3NF
Example 3 (Not in 3NF)
Scheme  {BuildingID, Contractor, Fee}
1. Primary Key  {BuildingID}
2. {BuildingID}  {Contractor}
3. {Contractor}  {Fee}
4. {BuildingID}  {Fee}
5. Fee transitively depends on the BuildingID
6. Both Contractor and Fee depend on the entire key hence 2NF
Third Normal Form (3NF)
Building
ID
Contractor Fee
100 Randolp
h
120
0
150 Ingersoll 110
0200 Randolp
h
120
0
250 Pitkin 110
0
300 Randolp
h
120
0

17.  Move all items involved in transitive dependencies to a new
entity.
 Identify a primary key for the new entity.
 Place the primary key for the new entity as a foreign key on
the original entity.
 Example 1 (Convert to 3NF)
 Old Scheme  {Title, PubID, PageCount, Price }
 New Scheme  {PubID, PageCount, Price}
 New Scheme  {Title, PubID, PageCount}
3NF - Decomposition

18. Example 2 (Convert to 3NF)
Old Scheme  {Studio, StudioCity, CityTemp}
New Scheme  {Studio, StudioCity}
New Scheme  {StudioCity, CityTemp}
Example 3 (Convert to 3NF)
Old Scheme  {BuildingID, Contractor, Fee}
New Scheme  {BuildingID, Contractor}
New Scheme  {Contractor, Fee}
3NF - Decomposition
Building
ID
Contractor
100 Randolp
h
150 Ingersoll
200 Randolp
h
250 Pitkin
300 Randolp
h
Contractor Fee
Randolp
h
120
0
Ingersoll 110
0
Pitkin 110
0

19.  BCNF does not allow dependencies between attributes that belong to candidate keys.
 BCNF is a refinement of the third normal form in which it drops the restriction of a
non-key attribute from the 3rd normal form.
 Third normal form and BCNF are not same if the following conditions are true:
 The table has two or more candidate keys
 At least two of the candidate keys are composed of more than one attribute
 The keys are not disjoint i.e. The composite candidate keys share some
attributes
Example 1 - Address (Not in BCNF)
Scheme  {City, Street, ZipCode }
1. Key1  {City, Street }
2. Key2  {ZipCode, Street}
3. No non-key attribute hence 3NF
4. {City, Street}  {ZipCode}
5. {ZipCode}  {City}
6. Dependency between attributes belonging to a key
Boyce-Codd Normal Form
(BCNF)

20. Example 2 - Movie (Not in BCNF)
Scheme  {MovieTitle, MovieID, PersonName, Role, Payment }
1. Key1  {MovieTitle, PersonName}
2. Key2  {MovieID, PersonName}
3. Both role and payment functionally depend on both candidate keys thus 3NF
4. {MovieID}  {MovieTitle}
5. Dependency between MovieID & MovieTitle Violates BCNF
Example 3 - Consulting (Not in BCNF)
Scheme  {Client, Problem, Consultant}
1. Key1  {Client, Problem}
2. Key2  {Client, Consultant}
3. No non-key attribute hence 3NF
4. {Client, Problem}  {Consultant}
5. {Client, Consultant}  {Problem}
6. Dependency between attributess belonging to keys violates BCNF
Boyce Codd Normal Form
(BCNF)

21.  Place the two candidate primary keys in separate entities
 Place each of the remaining data items in one of the resulting
entities according to its dependency on the primary key.
 Example 1 (Convert to BCNF)
 Old Scheme  {City, Street, ZipCode }
 New Scheme1  {ZipCode, Street}
 New Scheme2  {City, Street}
 Loss of relation {ZipCode}  {City}
 Alternate New Scheme1  {ZipCode, Street }
 Alternate New Scheme2  {ZipCode, City}
BCNF - Decomposition

22.  If decomposition does not cause any loss of information it is
called a lossless decomposition.
 If a decomposition does not cause any dependencies to be
lost it is called a dependency-preserving decomposition.
 Any table scheme can be decomposed in a lossless way into
a collection of smaller schemas that are in BCNF form.
However the dependency preservation is not guaranteed.
 Any table can be decomposed in a lossless way into 3rd
normal form that also preserves the dependencies.
 3NF may be better than BCNF in some cases
Decomposition – Loss of
Information
 Use your own judgment when decomposing schemas

23. Example 2 (Convert to BCNF)
Old Scheme  {MovieTitle, MovieID, PersonName, Role, Payment }
New Scheme  {MovieID, PersonName, Role, Payment}
New Scheme  {MovieTitle, PersonName}
• Loss of relation {MovieID}  {MovieTitle}
New Scheme  {MovieID, PersonName, Role, Payment}
New Scheme  {MovieID, MovieTitle}
• We got the {MovieID}  {MovieTitle} relationship back
Example 3 (Convert to BCNF)
Old Scheme  {Client, Problem, Consultant}
New Scheme  {Client, Consultant}
New Scheme  {Client, Problem}
BCNF - Decomposition

24.  Fourth normal form eliminates independent many-to-one relationships
between columns.
 To be in Fourth Normal Form,
 a relation must first be in Boyce-Codd Normal Form.
 a given relation may not contain more than one multi-valued attribute.
 Example (Not in 4NF)
 Scheme  {MovieName, ScreeningCity, Genre)
 Primary Key: {MovieName, ScreeningCity, Genre)
 All columns are a part of the only candidate key, hence BCNF
 Many Movies can have the same Genre
 Many Cities can have the same movie
 Violates 4NF
Fourth Normal Form (4NF)
Movie ScreeningC
ity
Genre
Hard Code Los Angles Comedy
Hard Code New York Comedy
Bill Durham Santa Cruz Drama
Bill Durham Durham Drama
The Code Warrier New York Horror

25.  Example 2 (Not in 4NF)
 Scheme  {Manager, Child, Employee}
 Primary Key  {Manager, Child, Employee}
 Each manager can have more than one child
 Each manager can supervise more than one employee
 4NF Violated
 Example 3 (Not in 4NF)
 Scheme  {Employee, Skill, ForeignLanguage}
 Primary Key  {Employee, Skill, Language }
 Each employee can speak multiple languages
 Each employee can have multiple skills
 Thus violates 4NF
Fourth Normal Form (4NF)
Manage
r
Child
Employe
e
Jim Beth Alice
Mary Bob Jane
Mary NULL Adam
Employ
ee
Skill Langua
ge
1234 Cooking French
1234 Cooking German
1453 Carpentry Spanish
1453 Cooking Spanish
2345 Cooking Spanish

26.  Move the two multi-valued relations to separate tables
 Identify a primary key for each of the new entity.
 Example 1 (Convert to 3NF)
 Old Scheme  {MovieName, ScreeningCity, Genre}
 New Scheme  {MovieName, ScreeningCity}
 New Scheme  {MovieName, Genre}
4NF - Decomposition
Movie Genre
Hard Code Comedy
Bill Durham Drama
The Code Warrier Horror
Movie ScreeningC
ity
Hard Code Los Angles
Hard Code New York
Bill Durham Santa Cruz
Bill Durham Durham
The Code Warrier New York

27. Example 2 (Convert to 4NF)
Old Scheme  {Manager, Child, Employee}
New Scheme  {Manager, Child}
New Scheme  {Manager, Employee}
Example 3 (Convert to 4NF)
Old Scheme  {Employee, Skill, ForeignLanguage}
New Scheme  {Employee, Skill}
New Scheme  {Employee, ForeignLanguage}
4NF - Decomposition
Manage
r
Child
Jim Beth
Mary Bob
Manage
r
Employe
e
Jim Alice
Mary Jane
Mary Adam
Employ
ee
Langua
ge
1234 French
1234 German
1453 Spanish
2345 Spanish
Employ
ee
Skill
1234 Cooking
1453 Carpentry
1453 Cooking
2345 Cooking

28.  Fifth normal form is satisfied when all tables are broken
into as many tables as possible in order to avoid
redundancy. Once it is in fifth normal form it cannot be
broken into smaller relations without changing the facts
or the meaning.
Fifth Normal Form (5NF)

29.  The relation is in DKNF when there can be no insertion
or deletion anomalies in the database.
Domain Key Normal Form
(DKNF)

30. SQL
 SQL, pronounced ‘Sequel’ or simply S-Q-L, is a
computer programming language that was
developed especially for querying relational
databases using a non-procedural approach.
 The term non-procedural means that you can
extract information by simply telling the system
what information is needed without telling how to
perform the data retrieval. The RDBMS parses
(converts) the SQL commands and completes the
task.

31. SQL
 Extracting information from the database by
using SQL is termed querying the database.
 SQL is a language that is fairly simple to learn,
in terms of writing queries but it has
considerable complexity because it is a very
powerful language.

32. DATA AND INFORMATION
 Information is derived from raw facts known as
data.
 Data has little meaning or usefulness to managers
unless it is organized in some logical manner.
 One of the most efficient ways to organize and
manage data is through the use of database
management system (DBMS).

33. DATA
 Two types of data are stored within a database
 User data : Data that must de stored by an
organization.
 System data: Data the database needs to
manage user data to manage itself. This is also
termed metadata, or the data about data.

34. SQL
 Data is manipulated by RDBMS users through
the use of special data manipulation language.
 Database structures can also be defined by the
use of data definition language.
 SQL is the most popular database language
and has commands that enable it to be used for
both manipulation and definition of databases.

35. SQL
 SQL is used by Oracle for all interaction with
the database. SQL statements fall into the two
major categories
 Data Definition Language(DDL) : Set of SQL
commands that create and define objects in a
database
 Data Manipulation Language(DML) : Set of
SQL commands that allow users to manipulate
the data in a database.

36. SQL
 SQL is basically a free format language. This
means that there are no particular spacing rules
that must be followed when typing SQL
commands.
 In Oracle, you must end each individual SQL
statement (irrespective of whether it is
composed as a single or multiple lines of code)
with a semi-colon (;). It is the “;” which ends
an SQL statement and tells Oracle to Execute it.

37. RELATIONAL
OPERATIONS
 SQL operations for creating new tables,
inserting table rows , updating table rows,
deleting table rows, and querying databases are
the primary means of interfacing with relational
databases.
 The SELECT statement is used primarily to
write queries that extract information from the
database which is a collection of related tables.

38. Starting Oracle SQL*PLUS
 The most common types used are either the
standard Oracle SQL*PLUS available for a
Windows-type interface or by connecting to an
Oracle database via a telnet session.
 The following Log On session is a connection to
an Oracle database stored on a Sun Microsystems
server running the Unix O/S.
 A SQL*PLUS session is begun by typing the
command sqlplus at the command prompt($) and
entering the username and password information .

39. Log On Screen

40. Exiting SQL*PLUS
 The SQL*PLUS session can be ended by
typing a command at the SQL prompt to
terminate the session.
 Two commands are available: exit or quit.
Either one of these can be used to terminate a
SQL*PLUS session.

41. Running (Executing) a Command
File
 The command to run (execute) a command file
is:
 SQL> START filename.sql
 A form of shorthand for the word “start” can be
used when executing a command file by
replacing “start” with the @ (“at” symbol).

42. Syntax Conventions
 Each select statement must follow precise
syntactical and structural rules.
 The following is the minimum structure and
syntax required for an SQL SELECT statement.
 SELECT [DISTINCT | ALL] {* | select_list}
FROM {table_name [alias] | view_name}

43. SQL Keywords
 Keywords are words that have a predefined
meaning in SQL.
 In practice, keywords may be entered in upper
or lower case letters.
 SELECT * FROM employee;
 select * from employee;

44. SQL Keywords
 In some cases keywords can be abbreviated.
 The allowed abbreviation is shown in upper case
letters with the remainder shown in lower case,
which means either the full word or only the
upper case part can be used.
 DESCribe: can be entered as either DESC or
DESCRIBE.

45. SQL Naming Conventions
 Identifiers are the names given by information
system developers or system users to database
objects such as tables , columns, indexes, and
other objects as well as the database itself.
 There are several rules for naming database
objects that must be followed.
 Identifiers should contain between 1 and 30
characters.
 The first character must be either alphabetic (a-z,
A-Z) or the @ symbol or _ (underscore).

46. SQL Naming Conventions
 After the first character, digits, letters, or the symbols
$,#, or _(underscore) must be used.
 No embedded spaces are allowed in identifiers.
 SQL keywords cannot be used as an identifier.

47. Using SQL Queries to Insert,
Update, Delete, and View Data:
Joining Multiple Tables

48. Lesson C Objectives
 After completing this lesson, you should be able to:
 Create SQL queries that join multiple tables
 Create nested SQL queries
 Combine query results using SET operators
 Create and use database views
48

49. Joining Multiple Tables
 a Join
 Combines data from multiple tables using foreign key
references
 Syntax
 SELECT column1, column2, …
FROM table1, table2
WHERE table1.joincolumn = table2.joincolumn
AND search_condition(s);
49
SELECT s_id, s_last, f_last
FROM student, faculty
WHERE student.f_id = faculty.f_id
AND f_last IN (‘Marx’, ‘Zhulin’);

50. Joining Multiple Tables
 Must qualify column name in SELECT clause
 Specify name of table that contains column followed by
period then column name
 Example: SELECT s_id, s_last, student.f_id
 Join condition
 Specifies table names to be joined and column names on
which to join tables
 Example: WHERE student.f_id = faculty.f_id
50

51. Inner Joins
 Simplest type of join
 Also called: Equality join, Equijoin, Natural join
 VALUES in one table equal to values in other table
 Query design diagram helps get the query right
51
SELECT s_id, s_last, s_first, student.f_id, f_last
FROM student, faculty
WHERE student.f_id = faculty.f_id;
Could be replaced by:
FROM Student NATURAL JOIN faculty;

52. 52
Display column, search column, join
column
 Display columns: appear in SELECT clause
 Search columns: appear in search condition
 Join columns: primary key and foreign key column on which
you join the tables.
 Linkage table: contains join column to link other tables
through foreign key values.
SELECT f_last
FROM faculty, course_section, term
WHERE faculty.f_id = course_section.f_id
AND course_section.term_id = term.term_id
AND term_desc = 'Summer 2007';

53. Deriving a SQL Query From a Query
Design Diagram
53
 4 tables, 3 links
 All 4 tables must be named in the
FROM clause
 Query must have 3 join conditions
because there are 3 links
 Always 1 fewer join condition than
number of tables that query joins.
 If you omit one join condition, the
query creates a Cartesian product
(every row in one table is joined with
every row in other table) with more
row than expected.
SELECT course_name, grade
FROM student, enrollment, course_section, course
WHERE student.s_id = enrollment.s_id
AND enrollment.c_sec_id = course_section.c_sec_id
AND course_section.course_no = course.course_no
AND s_last = 'Jones'
AND s_first = 'Tammy';
Search conditions

54. Outer Joins
 Inner joins return row only if values exist in all joined tables
 Outer joins return
 all rows from one table (called inner table) and
 only matching rows from second table (outer table)
 Syntax: inner_table.join_col = outer_table.join_col(+)
54
(+) operator signals Oracle to insert NULL for columns from the outer table with no matching rows in the
inner table.

55. Self-join
 Query that joins table to itself
 Must create table alias
 Alternate name assigned to table in query’s FROM clause
 Syntax: FROM table1 alias1, table1 alias2 …
55

56. Creating Nested Queries
 Nested query
 Consists of a main query and one or more subqueries
 Main query
 First query that appears in SELECT command
 Sub query
 Retrieves values that main query’s search condition
must match
 Sub query is evaluated first. Then, DBMS substitute
subquery’s output into main query.
56

57. Creating Nested Queries
57
Q: What would happen if a sub query generated
more values than the main query is expecting?

58. 58
Creating sub queries that return
multiple values

59. Using Multiple Sub queriesWithin
a Nested Query
 Use AND and OR operators
 To join search conditions associated with subqueries
59

60. Using SET operators to combine Query Results
 UNION
 Queries must have
same number of
display column in
their SELECT clause
 Corresponding display
columns must have
same data type
60
Note: S_LAST, S_FIRST, S_PHONE used as
display title even though there are faculty
members names displayed along with

61. 61
Using SET operators to combine Query Results
 INTERSECT
– Queries must have
same number of
display column in their
SELECT clause
– Corresponding display
columns must have
same data type
– Suppresses duplicates

62. 62
Using SET operators to combine Query Results
 MINUS
 Queries must have
same number of
display column in
their SELECT clause
 Corresponding display
columns must have
same data type
 Suppresses duplicates
 Finds difference
between two query
results

63. Creating and Using Database Views
 Source query
 Used to create view
 Specify subset of single table’s columns or rows or join multiple
tables
 Updatable views
 Can be used to update database
 Syntax
 CREATE VIEW view_name
 AS source_query;
 Or
 CREATE OR REPLACE VIEW view_name
 AS source_query;
63

64. Removing Views
 DROP VIEW command
 Remove view from user schema
 Syntax
 DROP VIEW view name;
64

65. References
1. http://www.tutorialspoint.com/sql/sql-rdbms-concepts.htm
2. http://ithopes.com/myblog/blog/simple-definition-normalization-
relational-database-management-system-rdbms-sql-server-oracle-
main-difference-terms-called-normalization-denormalization/
3. http://www.atlasindia.com/sql.htm
4. http://holowczak.com/database-normalization/
5. Database System Concepts: Abraham Silberschatz, Henry F. Korth
& S., Sudarshan, TATA Mcgraw Hill.
6. Database Systems Concepts, design and Applications 2/e, Singh S.
K, PearsonEducation
7. SQL- PL/SQL, Ivan bayross, BPB Publications.