history of database processing module 1 (2)
DESCRIPTION
TRANSCRIPT
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