History of database processing module 1 (2)

MODULE 1DATABASE MANAGEMENT SYSTEMS

HISTORY OF DATABASE PROCESSING

STAGES

• Organizational Context (1960)• Relational Model (1970)• Object Oriented DBMS (1980)• Client Server Database Application (1990)• Database using internet Technology (200)

Organizational Context (1960)

Used to solve file processingDifficulty in managing dataDifficulty in developing new systemsLimitations in Integration of data

Companies started developing large database

Started centralizing operational data

Started Organization

wide Database

Application

Limitations

• Limited Technology• New Technology• Slow Applications• Unreliable Applications• Difficulty in Handling large Volume of Data• Slow Transactions• Unreliability of Database

What made the situation to improve ?

• More Education on Hardware and Software• More experts evolved• New methods of: controlling data

: protecting data : backing of database

Evolutions

Navigational DBMS

Integrated Data Store

(Charles Bachman)

IMSBy: IBM

Parent

Root

Relational Model (1970)

• Used application of mathematics: Relational Algebra

• Used to reduce the problem of storing large amount of data

• Developed by E.F.Codd

Benefits

• Minimizes duplication• Eliminates processing & storing Errors• Data stored as tables: rows & columns• Concept of normalization used• Columns of 1 row relates the entities

Order Number

Customer First Name

Customer Last Name

Item

A1010 John Markose Chair

A1011 Martin Baby Tables

A1012 Thomas Stephen Cupboard

A1013 Peter Edwin Computer

Resistance to Relational Model

• Requires more computer resources• Makes the system slow• Impractical with less speed processing capacity• Examples: INGRES,

PRTV, Business System 12Alphora Dataphor, Rel

Object oriented DBMS

An object-oriented database management system (OODBMS), sometimes shortened to ODBMS for object database management system), is a database management system (DBMS) that supports the modelling and creation of data as objects.

What is an object ?

• objects are key to understanding object-oriented technology

• Examples:• dogs have • state (name, color, breed, hungry) and • dogs have behavior (barking, fetching, and

slobbering )

Examples:

• Bicycles have • state (current gear, current pedal cadence,

two wheels, number of gears) and • behavior (braking, accelerating, slowing down,

changing gears).

Object

• Definition: An object is a software bundle of variables and related methods.

Drawbacks

• Difficult to use• Very expensive to develop• Already data in relational model needs

conversion• More suitable for engineering application

Client Server Database Application (1990)

• A client/server application is a piece of software that runs on a client computer and makes requests to a remote server.

• “Client/server systems operate in a networked environment, splitting the processing of an application between a front-end client and a back-end processor.”

Basic Elements

• A CSDB system consists of three primary software components:

• the client application (also called the front end),

• the data access layer (also called middleware), and

• the database server (also called a database engine, DBMS, data source, or back end).

Client Application

• The client application is responsible for accepting input from the user, submitting a query to the database server based on that input, receiving results from the server, formatting them, and presenting them to the user.

Data Access Layer

The data access layer is relatively transparent to the user, but may be very apparent to the developer of the client app. It provides for the application and API used to submit queries to a data source .

Database Server

The database server accepts queries from clients, processes them concurrently, and returns results. There are a number of different query languages around, by far the most prevalent of which is SQL

Problems

Security

Connectivity

Technical Support

Database Models

• Hierarchical DBMS Model• Network DBMS Model• Relational DBMS Model• Object Oriented DBMS Model• Multi dimensional DBMS Model

• The hierarchical data model organizes data in a tree structure.

• There is a hierarchy of parent and child data segments.

• This structure implies that a record can have repeating information, generally in the child data segments.

• Data in a series of records, which have a set of field values attached to it.

• It collects all the instances of a specific record together as a record type.

• These record types are the equivalent of tables in the relational model, and with the individual records being the equivalent of rows.

A hierarchical database consists of the following:• It contains nodes connected by branches.• The top node is called the root.• If multiple nodes appear at the top level, the

nodes are called root segments.• The parent of node is a node directly above a

node• Each node (with the exception of the root) has

exactly one parent.• The child of node is the node directly below the

node and connected by a branch.• One parent may have many children.

Network Model

• The network database organizes data in a network structure.

• Any column in the network structure can be linked to any other like a tree structure.

• A network structure can be described in terms of parents and children.

• This model allows having more than one parent.

Network Model

• Network DBMS have found not much more acceptance than the hierarchical DBMS.

• They have the same flexibility limitations as hierarchical database:

• the more powerful structure for representing data relationships allows a more realistic modeling of geographic phenomena.

• However network database tend to become overlay complex too easily.

Relational Model

• The relational database organizes data in tables.• Each table is identified by a unique table name,

and is organized by rows and columns. • Each column within a table also has a unique

name. Columns store the values for a specific attribute

• Rows represent one record in the table.

Properties of Relational Tables:

• Values Are Atomic• Each Row is Unique• Column Values Are of the Same Kind• The Sequence of Columns is Insignificant• The Sequence of Rows is Insignificant• Each Column Has a Unique Name

One-to-one Relationship-

• One-to-one Relationship- Here one and only one record in the

destination table is related to one and only one record in the source table.

One to one relationship

One-to-Many Relationship-

• This means that one record in the destination table may be related to more than one record in the source

One-to-Many Relationship-

Many-to-One Relationship

• This type of relationship is just opposite to the One-to-Many Relationship. Here two or more records in the destination table may be related to one record in the source table.

Many-to-One Relationship

Object Oriented Model

• The object oriented data model manages data through object.

• An object is a collection of data elements and operations that together are considered as single entity.

Multi Dimensional Database Model

• A multidimensional database (MDB) is a type of database that is optimized for data warehouse and online analytical processing (OLAP) applications.

• Multidimensional databases are frequently created using input from existing relational databases. Whereas a relational database is typically accessed using a Structured Query Language (SQL)

DATABSE COMPONENTS

• Data Repository• DBMS• Hardware• Procedure Interface• Application Software• Practitioners• Data Dictionary

• System Software• Network Application• Front Tools • Users

APPLICATION INTERFACE

PROCEDURE INTERFACE

APPLICATION SOFTWARE

QUERY REPORTINGFRONT END

TOOLS

DBMSDATA

REPOSITORY

DATA DICTIONARY

HARDWARE

USERSPRACTIONERS

DATABASE COMPON-

ENTS

Data Repository

• Data Repository is a logical (and sometimes physical) partitioning of data where multiple databases which apply to specific applications or sets of applications reside.

Procedure interface

• The characteristics of a procedure that is executed on the database

• ExampleSQL:>/ CREATE TABLE <Table name>

Data Dictionary

• A data dictionary is a collection of descriptions of the data objects or items in a data model for the benefit of programmers and others who need to refer to them.

Data dictionary : sample

Database Development Process

Enterprise data modelling

• Is the first step in database development, in which the scope and general contents of organisational databases are specified

• Graphical representation of data used by an enterprise or company

• Gives a helicopter view of the data and data transactions of the organisation

•

Enterprise data modelling

• Data model encompass both current and historical data of the organisation

• The model should reflect both the data and the processes of the organisation, plus the views of these components required by the various sections of the organisation.

• Example:• sales data (invoices etc.) will be viewed from a monetary

aspect by the accountant, from a quantitative aspect by the store staff and from both these aspects by the marketing people

Information System Architecture (ISA)

6 Key Components:1. Data2. Process3. Network4. People5. Events and points in Time6. Reason

1. Data

The processed information The information that need to be exchanged,

recorded, processed and verified, and classified and stored.

2. Process

• The event that manipulates the dataExample:Pos (Point of Sales): Billing of itemsBank : withdrawal or deposit of money by a

customer

3. Network

• Network transports the data around the organization and between the organizations and the key business partners.

4. People

• The entities who perform the process• They are the source of information and

receiver of informationExample: Pos: Sender of information: Billing clerk

Receiver of Information: Store manager

5. Events and points in time

6. Reasons

• Reasons for events• Rules that govern the process• Example: Customer cash withdrawal at ATM

ATM transactionSl. No Event Process Action

1 Enter Pin Verify Pin Authorize

2 Enter Transaction Type

Choose Transaction

Authenticate

3 Enter Amount

Verify balance

Allow Withdrawal

enterprise data model (Pine Valley Furniture Company)

Information Engineering• “A data-oriented methodology to create and maintain

information systems.”• Top-down planning approach.• Four steps:– Planning (Results in an Information Systems Architecture)– Analysis – meet the various members of the organisation

(from top to bottom) to discuss and agree on the data requirements and the processes involved

– Design– Implementation

Information Engineering Planning phase

1. Identify Strategic Planning Factorsa. Goalsb. Critical Success factorsc. Problem Areas

Information Engineering Planning phase

2. Identify Corporate Planning Objectsa. Organizational Unitsb. Locationc. Business Functionsd. Entity Types

Information Engineering Planning phase

3. Develop Enterprise Modela. Functional decompositionb. Entity- Relationship diagramc. Planning Matrices

Example of process decomposition of an order fulfillment function

Planning matrices

• Provide an explicit approach for describing business requirements

• Location to function (which business function is being performed at which location)

• Unit to function (which business functions are the responsibility of which business units)

• IS application to data entity (explains how each information system interacts with each data entity)

Planning matrices

• Supporting function to data entity (which data are captured, used, updated, deleted within each function)

• IS application to business objective (shows which information systems support each business objective)

Systems development life cycle (SDLC)

• Is a complete set of steps that a team of IS professionals follow to specify, develop, maintain and replace information systems

• Process is often viewed as a cascade of steps (see following figure)

• Cascade or ‘waterfall’ approach as each step flows into the next – though steps can overlap in time and it is possible to backtrack when prior decisions need to be reconsidered

Database development activities during the SDLC

Project Identification and Selection

Project Initiation and Planning

Analysis

Physical Design

Implementation

Maintenance

Logical Design

Phase 1: Project identification and Selection:

Purpose

• Understanding Business situation

Deliverables

• Formal request to conduct project design, and develop information system

Phase 2: Project Initiation & Planning

Purpose

• Stating Business situation

• Stating how information system solves the problem

• Stating the opportunity by using information system

Deliverables

• Written request to study the possible changes to existing system or the development of a new system

Phase 3: Analysis

Purpose

• Analyze Business situation

• Determining requirements

• Structuring requirements

• Selecting competing system features

Deliverables

• Functional specification of system

• Meeting user requirements

• Meeting feasibility to develop the system

• Feasibility to implement the system

Phase 4: Logical Design

Purpose

• To elicit and structure all information requirements

Deliverables

Detailed functional specification of :

a. Datab. Formac. Reportsd. Displayse. Processing Rules

Phase 5: Physical design

Purpose

• To develop technology and Organizational specifications

Deliverables

• Computer Program• Database structures• Technology purchase• Physical site plans• Organizational

redesigns

Phase 6: Implementation:

Purpose

• To write programs• Build data files• Test & install new

system• Train users• finalize

documentation

Deliverables

• Programs that work accurately to specification

• Documentation• Training materials

Phase 7: Maintenance

Purpose

• Monitor operations and usefulness of system

• Repair and enhance the system

Deliverables

• Periodic audits to check the accuracy of the system

Database development stages/ phases

1. Enterprise Modeling2. Conceptual data modeling3. Logical database design4. Physical database design and

definition5. Database Implementation6. Database maintenance

1. Enterprise Modeling

• Analyze current data processing• Analyze general functions and their database

needs• Justify need for new data and database in

support for business

2. Conceptual data modeling

• Identify scope of database requirement• Analyze overall data requirement• Develop preliminary conceptual data model• Compare preliminary conceptual data model

wit enterprise data model• Develop conceptual data model including all

entities , relationships, attributes and business rules

3: Logical database design

• Analyze- transactions, forms, displays, and inquiries and database views.

• Integrate database views into conceptual data model

• Identify data integrity & security requirements

• Create stable & well defined structure for database

4. Physical database design & definition

• Define database to DBMS• Decide on physical organization of data• Design database processing programs

5. Database Implementation

• Code & test database processing programs• Complete database documentation & training

materials• Install database and convert data from prior

systems

6. Database Maintenance

• Analyze database and database applications to ensure that evolving information requirements are met

• Tune database for improved performance• Fix errors in database and database

applications and recover database when it is contaminated.

Lets wind up…………..

• Data, Database, Database Management System• Relationship of application programs with DBMS• Definition of database• Short history of database processing• Types of database• Components of database system• Creating the database• Developing databases