Unit 5 Introduction to Oracle and Sql.pptx

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In this presentation explain about Functions and Normalisation

INTRODUCTION TO ORACLE AND SQL
UNIT-5
S. Vasuki, M.C.A.,
Assistant Professor,
Department of Computer Science
Sri Sarada Niketan College of Science for Women,
Karur.

Unlocking the Power of SQL
Functions
Welcome to our SQL Functions workshop! Today, we'll explore the versatility
of SQL functions and how they can be leveraged for data manipulation and
analysis.

Introduction to SQL Functions
Function Definition
A function is a pre-defined SQL code
block that performs a specific operation
on data.
Function Categories
SQL functions can be broadly
categorized as single-row and group
functions.
Function Benefits
Functions enhance data manipulation,
enable complex calculations, and
improve code readability.

Single Row Functions
1 String Functions
Functions like LENGTH,
SUBSTRING, and UPPERcase
manipulate text data.
2 Numeric Functions
Functions like ROUND, ABS,
and SQRT perform
calculations on numeric
data.
3 Date Functions
Functions like DATE_ADD,
DATEDIFF, and DAYOFWEEK
handle date and time
operations.
4 Conversion Functions
Functions like CAST and
CONVERT change data types
between text, numeric, and
date formats.

Group Functions
SUM
Calculates the total value of a
column.
AVG
Calculates the average value of
a column.
COUNT
Counts the number of rows in a
table or the number of non-null
values in a column.
MIN, MAX
Finds the minimum and
maximum values in a column.

Reporting Aggregated Data
GROUP BY
Groups rows based on a specified
column.
HAVING
Filters the grouped data based on
specified criteria.

Displaying Data from Multiple
Tables
1 INNER JOIN
Returns rows where values in both tables match.
2 LEFT OUTER JOIN
Returns all rows from the left table and matching rows from the right table.
3 RIGHT OUTER JOIN
Returns all rows from the right table and matching rows from the left table.
4 FULL OUTER JOIN
Returns all rows from both tables, regardless of match.

Sub Queries
Correlated Sub Queries
Subqueries referencing the outer query's data.
Non-Correlated Sub Queries
Subqueries independent of the outer query.
Nested Sub Queries
Subqueries embedded within other subqueries.

Normalization
1
1NF
Eliminate repeating groups.
2
2NF
Eliminate partial dependencies.
3
3NF
Eliminate transitive dependencies.

Denormalization
1
Reduced Queries
Fewer joins needed for data retrieval.
2
Increased Performance
Faster access to data for reporting.
3
Data Redundancy
Increased storage needs and potential for data
inconsistency.

Best Practices for Database
Design
1
Consistency
Follow naming conventions and data
types.
2
Efficiency
Optimize for performance and
resource use.
3
Security
Implement access control and data
encryption.
4
Scalability
Design for future growth and data
volume.

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Unit 5 Introduction to Oracle and Sql.pptx

1. INTRODUCTION TO ORACLE AND SQL UNIT-5 S. Vasuki, M.C.A., Assistant Professor, Department of Computer Science Sri Sarada Niketan College of Science for Women, Karur.

2. Unlocking the Power of SQL Functions Welcome to our SQL Functions workshop! Today, we'll explore the versatility of SQL functions and how they can be leveraged for data manipulation and analysis.

3. Introduction to SQL Functions Function Definition A function is a pre-defined SQL code block that performs a specific operation on data. Function Categories SQL functions can be broadly categorized as single-row and group functions. Function Benefits Functions enhance data manipulation, enable complex calculations, and improve code readability.

4. Single Row Functions 1 String Functions Functions like LENGTH, SUBSTRING, and UPPERcase manipulate text data. 2 Numeric Functions Functions like ROUND, ABS, and SQRT perform calculations on numeric data. 3 Date Functions Functions like DATE_ADD, DATEDIFF, and DAYOFWEEK handle date and time operations. 4 Conversion Functions Functions like CAST and CONVERT change data types between text, numeric, and date formats.

5. Group Functions SUM Calculates the total value of a column. AVG Calculates the average value of a column. COUNT Counts the number of rows in a table or the number of non-null values in a column. MIN, MAX Finds the minimum and maximum values in a column.

6. Reporting Aggregated Data GROUP BY Groups rows based on a specified column. HAVING Filters the grouped data based on specified criteria.

7. Displaying Data from Multiple Tables 1 INNER JOIN Returns rows where values in both tables match. 2 LEFT OUTER JOIN Returns all rows from the left table and matching rows from the right table. 3 RIGHT OUTER JOIN Returns all rows from the right table and matching rows from the left table. 4 FULL OUTER JOIN Returns all rows from both tables, regardless of match.

8. Sub Queries Correlated Sub Queries Subqueries referencing the outer query's data. Non-Correlated Sub Queries Subqueries independent of the outer query. Nested Sub Queries Subqueries embedded within other subqueries.

9. Normalization 1 1NF Eliminate repeating groups. 2 2NF Eliminate partial dependencies. 3 3NF Eliminate transitive dependencies.

10. Denormalization 1 Reduced Queries Fewer joins needed for data retrieval. 2 Increased Performance Faster access to data for reporting. 3 Data Redundancy Increased storage needs and potential for data inconsistency.

11. Best Practices for Database Design 1 Consistency Follow naming conventions and data types. 2 Efficiency Optimize for performance and resource use. 3 Security Implement access control and data encryption. 4 Scalability Design for future growth and data volume.

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