Database Concepts 101

GileadSciences
Database Concepts

What is data, information, & Database?
 Data is a collection of facts, such as values or measurements.
 It can be numbers, words, measurements, observations or
even just descriptions of things.
 Data is information or facts that are collected to give a bigger
picture of things.
 Information has meaning in some context for its receiver
 A database is a collection of information that is organized
so that it can easily be accessed, managed, and updated

What is DBMS?
 DBMS is the data base management system which is
responsible for the storage of the data. Through this the
storage of data had been quite easy and the data that had
been stored can be easily modified and extracted too. This
in fact is the collection of the storing, executing, processing
and modifying the data.
 DBMS contains information about a particular enterprise
 Collection of interrelated data
 Set of programs to access the data
 An environment that is both convenient and efficient to use

DBMS Applications
 Database Applications:
 Banking: transactions
 Airlines: reservations, schedules
 Universities: registration, grades
 Sales: customers, products, purchases
 Online retailers: order tracking, customized
recommendations
 Manufacturing: production, inventory, orders, supply chain
 Human resources: employee records, salaries, tax
deductions

Drawbacks of using file systems
 Data redundancy and inconsistency
 Multiple file formats, duplication of information in different files
 Difficulty in accessing data
 Need to write a new program to carry out each new task
 Data isolation — multiple files and formats
 Integrity problems
 Integrity constraints (e.g., account balance > 0) become
“buried” in program code rather than being stated explicitly
 Hard to add new constraints or change existing ones
 Atomicity of updates
 Failures may leave database in an inconsistent state with partial
updates carried out
 Example: Transfer of funds from one account to another should
either complete or not happen at all

Drawbacks of using file systems
 Concurrent access by multiple users
 Concurrent access needed for performance
 Uncontrolled concurrent accesses can lead to inconsistencies
 Example: Two people reading a balance (say 100) and updating
it by withdrawing money (say 50 each) at the same time
 Security problems
 Hard to provide user access to some, but not all, data
Database systems (DBMS) offer solutions to all the above
problems

What is RDBMS?
 RDBMS is a database management system based on
relational model defined by E. F. Codd. Data is stored in the
form of rows and columns. The relations among tables are
also stored in the form of the table.
 Features: Provides data to be stored in tables
• Persists data in the form of rows and columns
• Provides facility primary key, to uniquely identify the rows
• Creates indexes for quicker data retrieval
• Provides a virtual table creation in which sensitive data can
be stored and simplified query can be applied.(views)
• Sharing a common column in two or more tables(primary key
and foreign key)
• Provides multi user accessibility that can be controlled by
individual users

What are E. F. Codd rules?
Also called Codd's Law, a set of 13 rules used to determine if a
DBMS can be considered a relational DBMS (RDBMS). In
1985, Dr. E. F. Codd first published this list of rules that
became a standard way of evaluating a relational system.
The rules have since been expanded by others, and after
publishing the original article Codd stated that there are no
systems that will satisfy every rule. Following are Codd's
original 13 rules:
0. Often referred to as rule 0, this rule states that all
subsequent rules are based on the notion that in order for a
database to be considered relational, it must use its
relational facilities exclusively to manage the database.
1. The Information rule: All information in an RDBMS is
represented logically in just one way - by values in tables.

What are E. F. Code rules?
2. The Guaranteed Access rule: Each item of data in an RDBMS
is guaranteed to be logically accessible by resorting to a
combination of table name, primary key value, and column
name.
3. The Systematic Treatment of Null Values rule: Null values
(distinct from an empty character string or a string of blank
characters and distinct from zero or any other number) are
supported in a fully relational DBMS for representing missing
information and inapplicable information in a systematic way,
independent of the data type.
4. The Dynamic Online Catalog Based on the Relational Model
rule: The database description is represented at the logical
level in the same way as ordinary data, so that authorized
users can apply the same relational language to its
interrogation as they apply to the regular data.

5. The Comprehensive Data Sublanguage rule: A relational
system may support several languages and various modes of
terminal use (for example, the fill-in-blanks mode). However,
there must be at least one language whose statements are
expressible, per some well-defined syntax, as character strings
and whose ability to support all of the following is
comprehensible: data definition, view definition, data
manipulation (interactive and by program), integrity
constraints, and transaction boundaries (begin, commit, and
rollback).
6. The View updating rule: All views of the data which are
theoretically updatable must be updatable in practice by the
DBMS.
7. The High-level Insert, Update, and Delete rule: The capability
of handling a base relation or a derived relation as a single
operand applies not only to the retrieval of data but also to the
insertion, update, and deletion of data.

8. The Physical Data Independence rule: Application programs
and terminal activities remain logically unimpaired whenever
any changes are made in either storage representations or
access methods.
9. The Logical Data Independence rule: Application programs
and terminal activities remain logically unimpaired when
information preserving changes of any kind that theoretically
permit un-impairment are made to the base tables.
10. The Integrity Independence rule: Integrity constraints must
be definable in the RDBMS sub-language and stored in the
system catalogue and not within individual application
programs.

11. The Distribution Independence rule: An RDBMS has
distribution independence. Distribution independence implies
that users should not have to be aware of whether a database
is distributed.
12. The Non-subversion rule: If the database has any means of
handling a single record at a time, that low-level language must
not be able to subvert or avoid the integrity rules which are
expressed in a higher-level language that handles multiple
records at a time

SQL
 SQL: widely used non-procedural language
• Example: Find the name of the instructor with ID 22222
select name
from instructor
where instructor.ID = ‘22222’
 Application programs generally access databases through
one of
• Language extensions to allow embedded SQL
• Application program interface (e.g., ODBC/JDBC) which allow SQL
queries to be sent to a database
 Two classes of languages
• Procedural – user specifies what data is required and how to get
those data
• Declarative (nonprocedural) – user specifies what data is required
without specifying how to get those data

Data Manipulation Language (DML)
 Language for accessing and manipulating the data
organized by the appropriate data model
• DML also known as query language

Data Definition Language (DDL)
 Specification notation for defining the database schema
 DDL compiler generates a set of table templates stored in a
data dictionary
 Data dictionary contains metadata (i.e., data about data)
• Database schema
• Integrity constraints
– Primary key (ID uniquely identifies instructors)
– Referential integrity (references constraint in SQL)
• Authorization
 Difference between Schema & User?
• HR Schema, Finance Schema, MFG…

Database Objects
Object Description
Table Basic unit of storage; composed of rows
and columns
View Logically represents subsets of data from
one or more tables
Sequence Numeric value generator
Index Improves the performance of some queries
Synonym Gives alternative names to objects

Data Types
Data Type Description
VARCHAR2(size) Variable length character data (32767
characters)
CHAR(size) Fixed Length Character data up to 2000
characters
NUMBER(p,s)
Variable length numeric data
DATE Date and time values
LONG Variable length character data up to 2GB
CLOB Character data up to 4GB

Data Model
A database model is a theory or specification describing how a
database is structured and used.
A collection of tools for describing
• Data
• Data relationships
• Data semantics
• Data constraints
Entity-Relationship data model
Object-based data models
Semi-structured data model (XML)
Other older models:
• Network model
• Hierarchical model

Database Design
The process of designing the general structure of the
database:
Logical Design – Deciding on the database schema. Database
design requires that we find a “good” collection of relation
schemas.
• Business decision – What attributes should we record in the
database?
• Computer Science decision – What relation schemas should we
have and how should the attributes be distributed among the various
relation schemas?
Physical Design – Deciding on the physical layout of the
database

Design Approach
 Normalization Theory: Database
normalization is usually performed when
designing a relational database
 Entity Relationship Model: ERD is the
commonly used system of diagramming,
for visual representation of the relational
model

Normalization
 Objective
 Eliminating redundant data (for example, storing the
same data in more than one table)
 Ensuring data dependencies make sense (only
storing related data in a table).
 Normalization typically involves decomposing an
un-normalized table into two or more tables that,
were they to be combined (joined), would convey
exactly the same information as the original
table.
 You'll often see 1NF, 2NF, and 3NF along with the
occasional 4NF.

Normalization Example
First Form: For a table to be in first normal form, all repeating groups
must be moved to a new table. Consider the example in Figure, in which
several office location columns have been added to the EMPLOYEE
table.

Second Form: Second normal form is a special-case normal form that
has to do with tables that have composite primary keys. A composite
primary key includes two or more columns. In second normal form, all
nonkey columns must depend on the entire primary key.
The EMPLOYEE_OFFICE_LOCATION table in Figure is in violation of
second normal form. For this table to comply with second normal form,
another table must be created and the OFFICE_PHONE_NUMBER data
must be moved to the new table.

Third Form: Third normal form expands on second normal form. It
dictates that every nonkey column must be a detail or a fact about the
primary key. Figure illustrates a third normal form violation.
The addition of the DEPT_NAME column in this EMPLOYEE table
violates third normal form in that DEPT_NAME is dependent on the
DEPT_ID value, not the EMPLOYEE_ID value. Complying with the rules
of third normal form necessitates creating another table and moving the
department name values into this new table, with a foreign key reference
from the EMPLOYEE table to the new table.

The Entity-Relationship Model
 Models an enterprise as a collection of entities and
relationships
• Entity: a “thing” or “object” in the enterprise that is distinguishable
from other objects, described by a set of attributes
• Attributes: All information about Entity
• Relationship: an association among several entities
 Represented diagrammatically by an entity-relationship
diagram:

Degrees of a Relationship
HusbandHusband WifeWife
Father ChildChild
BrotherBrother SisterSister
One-to-one (1:1)
One-to-many (1:n)
Many-to-many (n:m)

Many to One Mapping
CUSTOMER
TAKES
LOAN HAS REPAYMENT
C_ID C_NAME
LOAN_ID
LN_AMT
DT_OF_LOAN EMI_AMT
CHEQUE_ID
CHEQUE_DATE
CHEQUE_AMT
1 M
M
M

Query Processing
1. Parsing and translation
2. Optimization
3. Evaluation

Storage Management
 Storage manager is a program module that provides the
interface between the low-level data stored in the database
and the application programs and queries submitted to the
system.
 The storage manager is responsible to the following tasks:
• Interaction with the file manager
• Efficient storing, retrieving and updating of data

Database Users and Administrators
Database

Database System Internals

Client Server Architecture

Oracle Products
 Oracle Databases
 Oracle Application Server
 Oracle applications
 Oracle Collaboration Suite
 Oracle Developer Suite

Oracle Database 10g: “g” Stands for Grid
 Oracle’s grid infrastructure:
• Low cost
• High quality of service
• Easy to manage
Automatic
Storage
Management
Real
Application
Clusters
Oracle
Streams
Enterprise
Manager
Grid Control
Storage
grid
Database
grid
Application
grid
Grid
control

Oracle RDBMS Architecture
There are three main components:
1. Instance
- Instance memory/System Global Area (SGA)
- Back ground process
2. Database
- Data files
- Control Files
- Redo log files
3. Other Components
- Other process
- Other memory (PGA)
- Other files

System Development Life Cycle (SDLC)

GileadSciences
Avi Silberschatz
Henry F. Korth
S. Sudarshan

QUIZ
1. RDBMS?
Relational Database Management System
2. SQL?
Structured Query Language
3. Relational model defined by?
E. F. Codd
4. ER Model?
Entity-Relationship Model
5. Design Approach to reduce Duplication?
Normalization

Database Concepts 101

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