Database Management Unit-I

Published on January 2017 | Categories: Documents | Downloads: 37 | Comments: 0 | Views: 252
of 33
Download PDF   Embed   Report

Comments

Content

DATABASE MANAGEMENT SYSTEMS

UNIT – I

Introduction to Database Systems

Terminology
Data = known facts that can be recorded Database (DB) = logically coherent collection of related data with some inherent meaning
 

Entities such as students, courses, sections Relationships between entities such as students taking courses and sections being part of courses

Database management system (DBMS) = collection of programs that enable users to create and maintain a DB; general-purpose software system that facilitates process of defining, constructing, and manipulating DBs for various applications.

What is database?



A shared collection of logically related data and a description of this data, designed to meet the information needs of an organization
   

Data repository (data resource) Designed independently of applications (i.e., data abstraction) Long-term information needs at the enterprise level Primarily designed for quick and efficient data retrieval

What the Purpose for Learning about Database?


Paradigm shift: Data driven business environment

Production efficiencies

Knowledge and innovation (e.g., knowledge management, business intelligence)

Coordination of vendors (e.g., supply chain management

Competitor and marketplace information

Customer information (e.g., database marketing, CRM)

History (1)


Early 60s
  

Charles Bachman introduced first general purpose DBMS known as IDS (Turing Award 1973) at General Electric (GE) Integrated Data Store (IDS) formed the basis for N/w data model Network Data Model was standardized by the Conference on Data Systems Languages (CODASYL). IBM developed IMS Information Management Systems (IMS) formed basis for Hierarchical Data Model Hierarchichal Data Model SABRE system for making airline reservation jointly by IBM and American Airlines (allowed several people to access the same data thro’ computer N/W) Edgar Codd, at IBM proposed Relational Data Model (Turing Award 1981) Use of DBMSs for managing corporate data became standard practice



Late 60s
   



70s
 

History (2)


80s
  

Relational Data Model became dominant DBMS paradigm SQL query language for relational DBs developed as part of IBM’s System R project – is now the standard query language Transaction Management (concurrent execution of db programs) (James Gray, Turing Award 1999) Object-oriented Data Model Data warehouse and data mining Accessing databases through the web/internet Multimedia data Text data (information retrieval) Structure of the data (XML)



Now
    



Traditional File-Based System


Definition: "A collection of application programs that perform services for the end-users such as the production of reports. Each program defines and manages its own data."

Customer transactions Program Report

Operating expenses Program Report

Inventory

Vendors

Payroll

Program Report

Program Report

Program Report

One file, one application

Data Redundancy



Customer Order File
    

Invoice number Customer account number Customer name, address, city, state, zip code Order date Product code, product description, price, unit



Customer Account File
 

Account Number Customer name, mailing address, city, state, zip code



Customer Mailing List File


Customer name, mailing address, city, state, zip code

File-Based Systems



Records contain logically related data



Limitations:
 

Separation and isolation of data (one file, one program) Duplication of data  Loss of data integrity - uncertainty of the correct version of data and no consistency Data dependence - application program defines the data Incompatibility of file formats Fixed queries/proliferation of application programs - little flexibility in meeting changing information needs

  

Database


“A shared collection of logically related data (and a description of this data), designed to meet the information needs of an organization.”

Data and Data Definitions Central Repository Separation Applications

Data Abstraction


Separation between the data’s structure (definition) and the application programs

Application programs can be run on either the clients or server

Applications
Data and Data Definitions Central Repository DBMS

Organizing Data
 

Entity - distinct object (i.e., person, place, thing, concept or event) Attribute - describes some aspect of the entity (object)


Property of the entity



Relationship - association between entities

Entity
Customers Account_number Name Address

Entity
Purchases Invoice_number Account_number Purchase_date

Attributes

Relationship

Database

Management Queries
Customer Orders Order Items Products Manufacturers

DBMS
• DDL • DML • Controlled access Single Access Point

Application Programs

Central Repository (Organizational resource)

Other Software Multitude of Applications

Advantages of the Database Approach
  

      

Control of data redundancy Data consistency Efficient data access, Greater informational gain, more information from the same amount of data Sharing data, organizational resource (i.e., shared resource) Improved data integrity, validity and consistency Improved access and security Enforcement of standards Concurrency Access and Crash recovery Data Administration Reduced Application development time

Database Applications
Traditional database applications (banks, library catalogs, inventory, airlines, universities) Multimedia databases (images) Geographic information systems Data warehouse and online analytical processing (OLAP) Real time and active database technology (sensor systems, safety-critical systems) World wide web (e-commerce, internet banking)













DBMS Available

   




ORACLE DB2 – by the IBM MS-SQL Teradata Sybase Informix

Data Model




Collection of high level data description constructs that hide many low-level storage details Semantic data model


More abstract, high level data model (makes it easier to describe about the data)  Widely used one is ER model – pictorially denotes entities and relationships among them



Relational Model


Relation – set of records Schema  A description of data in terms of a data model is schema  Schema for a relation specifies its name, name of each field (or attribute or column) and type of each field.  Example


• Students(sid: string, name: string, login: string, gpa: real)

Each row in the relation is a record that describes the student

Other Data Models


  



Relational Data model ( dominant model) Hierarchical data model Network model Object – oriented model Object –relational model

Types of Database Models

HIERARCHICAL

COLUMN

ROW

VALUE

TABLE

RELATIONAL

Database Architecture/ Levels of Data Abstractions

External level (individual user views) Conceptual level (community user view)

Internal level (storage view) Database



Conceptual Schema
  

Describes data in terms of the data model of the DBMS. In a RDBMs, the conceptual schema describes all relations that are stored in the database. Eg. University Db
• Students (sid: string, name: string, gpa: real) • Faculty (fid: string, fname: string, sal: real)



Physical schema
  

Specifies additional storage details Summarizes how the relations described in conceptual schema are actually stored on secondary storage devices like disks and tapes Decide on what file organizations to use to store relations and indexes to speed up data retrieval operations



External Schema


Allow data access to be customized at the level of individual users or groups of users.

An Example of the Three Levels

SNo

FName

LName

Age

Salary

BranchNo
struct STAFF { int staffNo; int branchNo; Internal View char fName[15]; char lName[15]; struct date dateOfBirth; float salary; struct STAFF *next; /* pointer to next Staff record */ }; index staffNo; index branchNo; /* define indexes for staff */

Conceptual View

SNo

FName

LName

Age

Salary

External View1

SNo

LName

BranchNo

External View2

Database Design Phases

DATA ANALYSIS Entities - Attributes - Relationships - Integrity Rules

LOGICAL DESIGN

Tables - Columns - Primary Keys - Foreign Keys

PHYSICAL DESIGN DDL for Tablespaces, Tables, Indexes

Data Independence



Ability to change one schema level without affecting the higher level schemas


Physical Data Independence  Ability to change physical schema or internal schema without affecting conceptual or logical schema Logical Data Independence  Ability to change logical schema without affecting External or view schema. (application programs)



One imp. Adv of DBMS is data independence

Characteristics of the DB approach (1)


Single repository of data defined once, maintained and accessed by users Self-describing nature of DB
DB + description of DB structures and constraints metadata (stored in catalog)



stored in primary DB


DBMS software works with any number of DB applications
Insulation between programs and data, and data abstraction







Program--data independence Program--operation independence (OO DBMS) Abstraction: conceptual representation of data, no details of how data is stored or operators are implemented

Characteristics of the DB approach (2)


Data model
  

Relational data model Object-oriented data model Entity-relationship data model



Support multiple views of data
view = subset of DB virtual data derived from DB (not explicitly stored)



Sharing data and multi-user transaction processing
 

Concurrency control Online transaction processing (OLTP)

Query Languages


Query → questions involving data stored in dbms Relational Algebra




formal query language based on collection of operators for manipulating relations formal query language based on mathematical logic Defines db structure Commands used are for creating, altering, query data



Relational Calculus




DDL: Data Definition Language
 



DML: Data Manipulation Language
 

For manipulating (inserting, deleting, updating) db contents Procedural and Non – procedural (Declarative) DML

Types of DML


Procedural DML  Must be embedded in a programming language. Searches for and retrieves individual db records and uses looping and other constructs of the host programming language to retrieve multiple records Non-Procedural or Declarative DML  Can be used as a stand-alone query language or can be embedded in a programming language. Searches for and retrieves information from multiple related db records in a single command



Components of a Database Environment
    

Hardware Software: DBMS, application program and query software Data: Organized in a schema, partitioned into subschemas Procedures: Govern the design, access and use of the database People: Administrators (DA, DBA), designers (logical and physical), application developers and users (novice and high-powered)

Database System
Users

DATABASE

Application Programs/Queries

SYSTEM DBMS Software Software to process queries/programs
Software to access stored data

Stored Data Defn.
(META-DATA).

Stored Database

Users of the Database
Day-to-day use of the DB
  



Database administrators (DBA) Database designers End-users  Casual end-users  Naïve or parametric users  Sophisticated end-users  Stand-alone users System analysts and application programmers (software engineering)

Implications of the DB approach



Potential for enforcing standard Reduce application development time Flexibility Availability of up-to-date info







When not to use a DBMS



Unnecessary overhead costs
 

Security, concurrency control, recovery and integrity High initial investment in hardware, software, training



DB and applications are simple, well defined, not expected to change Real-time requirements not met (due to overhead) Multi-user access not required





Sponsor Documents

Or use your account on DocShare.tips

Hide

Forgot your password?

Or register your new account on DocShare.tips

Hide

Lost your password? Please enter your email address. You will receive a link to create a new password.

Back to log-in

Close