Transcript Business Computing - Kendriya Vidyalaya Churu : Official

Business Computing
1. Computing:- Computing applies a set of
techniques on data/ instructions to define
and solve problems pertaining to a
specific information-based task.
2. Business Computing:-Computing
applied to solve business related
problems, is known as business
computing.
Open Source Software is a part of
business computing.
Business Application Areas
(a) Payroll Processing
(b) inventory control system:- Inventory is the
means by which items are identified priced and
tracked .Inventory control Management system
is designed to maintain the optimum inventory
levels , control, Inventory costs and track
merchandise movement .It provides the tools
needed to minimize Inventory levels and out-ofstock conditions and maximize valuable
management Information and profitability.
Terminology
• OSS:- Open Source Software
• OSI:- Open Source Initiative
• FLOSS:- Free Libre/ Livre and Open Source
Software
• FSF:-Free Software Foundation
• GNU:- GNU’s Not Unix
• W3C:- World Wide Web Consortium
• LAMP:- Linux Apache MySQL and PHP
• OLTP:- On-Line Transaction Processing
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OOo:- OpenOffice.org
HTTP:- Hyper Text Transfer Protocol
PHP:- Hypertext Pre-Processor
GPL:- General Public License
Information System Terminology :
TPS:-Transaction Processing System
MIS:- Management Information System
DSS:-Decision Support System
ESS:-Executive Support System
HRDS: Human Resource Development
System
Definitions
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OSS:- OSS refers to Open Source Software, which
is modifiable, redistributable software. But it may not
be free of charge.
FLOSS :- FLOSS refers to free Libre and Open
Source Software or to Free Livre and Open Source
Software. He term FLOSS is used to refer to a
software which is both free
Software as well as open source software
GNU :- GNU refer to understand the role of GNU in
free and open source software ,gnu project
emphasizes on freedom and thus its logotype show
a gnu , an animal living in freedom
• Freeware :-The term freeware has no clear
definition ,but is generally used for software ,
which is Available free of cost and which allows
copying and further distribution but not
modification those source code is not
available .Freeware should not be mistaken for
open software or for Free software.
• Shareware:- Shareware is software is made
Available with the right to redistribute copies,
but it is stipulated that if one intends to use the
Software, often after a certain period of time ,
then a license fee should be paid
•Free Software:- Free Software means the software
is freely accessible and can be freely used, changed
and distributed by all who wish to do so. Open
source software is different from free software in the
sense that it does not have free of charge.
•The Differences Between Hardware, Software
And Firmware:-
Hardware are the physical tangible components of a
computer system.
Software are the computer programs that govern the
operation of computers.
Firmware are the prewritten programs permanently
stored in read-only memory. These configure the
computer and are not easily modifiable by the user.
SDLC
• SDLC:- system development life cycle
is the traditional system development
methodology which consists of these
activities:
– I) Preliminary Study.
– ii) Feasibility Study.
– iii) Investigation& Fact Recording.
– iv) Analysis.
– v) Design.
– vi) Implementation And
– viii) Maintenance And Review.
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Preliminary study:- it is concern with determining
whether or not the new system should be
developed.
Feasibility study: -it determines whether the whole
process of system development is worth the effort
for organization or not. it studies the new system’s
feasibility in term of technical , operational and
economical performance.
Analysis: - it begins with gathering information
using any of these technical methods: interviewing,
questionaries,on-site observation,sampling etc.
System design:- it concern with designing of
various elements like
outputs,procedures,inputs,files etc.
DATABASE CONCEPTS
Definition:• Database:- A database is a collection of interrelated data
stored together to serve multiple applications;
• Database Management System (DBMS):-Database
management system is basically record computer based
record keeping system.
• Advantage of DBMS:- Database systems help:1. Reduce Data Redundancy,
2. Controlled Data Inconsistency,
3. Facilitate To Sharing Of Data,
4. Standardization Of Data,
5. Data Security.
6. Integrated Data.
Definition of Keys
• Primary Key:- A primary key is a set of one or more
attributes that can uniquely identify tuples (rows)
within the relation/table. For example, Roll_no# is a
primary key of “student_rec” table.
• Candidate Key:- All attributes combines inside a
relation that can serve as a primary key are Candidate
Keys as they are candidates for the primary key
position.
• Alternative Key:- A candidate key that is not the
primary key is called an alternative key. For example,
student_name is a alternative key in “student_rec”
table.
• Foreign Key:- A non key attribute, whose values are
derived from the primary key of some other table, is
known as Foreign Key in its current table.
• Referential Integrity:-Referential Integrity is a
system of rules that a DBMS uses to ensure that
relationships between records in related tables are
valid, and that users don’t accidentally delete or
change related data.
View:- View is a (virtual) table that does not really
exist in its own right but it is instead derived from
one or more underlying base table(s).
Views are like windows through which you view
desired information that is actually stored in a
base table.
Normalization:Normalization is the process of transformation of the
conceptual schema (logical data structures) of the
database into a computer representable from.
In other words, the normalization process helps in
attaining good database design thereby avoiding
undesirable things like repetition of information, inability
to represent information, loss of information etc.
Type of Normalization
•
First Normalization:- A relation R is in first
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normal form(1NF) if and only if all underlying domains
of the relation contain atomic (indivisible ) values.
I-NF perform following:1. Removing all repeating groups form the relation.
2. Decompose non-atomic attributes to atomic attributes.
3. All key attributes defined and all attributes depends on primary key.
Fig.—
• Second Normal Form (2NF):-A relation R is
in Second Normal Form(2NF) if and only if it is 1NF
and every non key attribute is fully dependent on the
primary key.
2NF perform following:1. In I-NF.
2. Includes no partial dependencies.
3. Still possible to exhibit transitive dependencies.
Fig.—
J
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J
K ( K is functionally dependent)
J
L ( L is no functionally dependent on J)
K
L
X
1
0
X
1
6
Y
4
1
Y
4
9
Z
3
5
• Third Normal Form (3NF):-A relation R is
in Third Normal Form(3NF) if and only if it is
2NF and every non key attribute is non
transitively dependent upon the primary
key.
– 2NF perform following:• In 2-NF.
• Contains no transitive dependencies
Boyce - Codd Normal Form (BCNF):-A relation R is
in Boyce - Codd Normal Form(2NF) if and only if it is
3NF and all of its determinants are candidate keys .
BCNF perform following:•In 3NF.
•Every determinant in the table is a
candidate key.
Advantage of Normalization
 It reduces data redundancies.
 It help eliminate data anomalies.
 It produces controlled redundancies to link
tables.
Need of Normalization:- Normalization is
needs for : Most databases to grow by adding new attributes
and new relations.
 For improving a efficiency of database.
 Minimizing the need for rewriting the application
programs (Front end)
DDLC
•
DDLC refers to Database Development Life
Cycle. It is the set of activities that are
carried out to develop and implement
databases
The stages of DDLC can be summarized as
following :1. Information Collection
2. Conceptual Data Modeling
3. Logical Data Modeling
4. Physical Data Modeling and Refinement
5. Data base Installation
Data Base Management System
• Entity Relationship (ER) model : ER model is a high level
conceptual model that describes data as entities, attributes and
relationships.
• Entity : It is an object that exists and is distinguishable from
other objects.
• Dependent Entity : An entity that depends upon other entity for
its existence. It is also called weak entity.
• Strong Entity : An entity that can exist on its own and does not
depend upon other entities for its existence.
• Attribute : An attribute is a property of a given entity.
• Composite Attribute : An attribute which is a group of
properties that can be decomposed further, is called composite
attribute.
• Sub entities And Super entities:-A subentity (or subtype) is
dependent entity of a superentity. And the attributes of the
superentity always apply to all its subentites but the converse is
not true
• Single-Valued and Multi-Valued attributes:Attribute can either be single-valued if they are
capable of storing single value or multi-valued if
they are capable of storing multiple values.
Example: Class, Roll_No are Single Valued
Attributes but Subject is a multi valued attribute.
• Schema:- it is the collection of database objects
of a user.
• Schema objects:- these are the logical
structures that directly refer to the database’s
data.
• Relation. A relation is a table having atomic
values, unique rows and unordered rows and
columns.
• Tuple. A row in a relation is known as tuple.
• Relationship : It is an association among
several entities
DFD
• Flow Chart : Graphical representation of an operation or a
process is called a flow chart.
• Process Chart : A process chart is a chart enlisting each
step of the process alongwith its activity type, time taken
and volume involved.
• Data Flow Diagram (DFD) : Graphical representation of a
system’s data and how the process transform the data is
known as Data Flow Diagram (DFD).
• Decision Table : A decision table is a chart with four
sections listing all logical conditions and actions in a system.
• Decision Tree : It is a diagram that lists conditions and
corresponding actions in the form of a tree with branches.
• Purpose of DFD Data flow diagram is a diagram used for
depicting data flows taking place in the system. Data flow
analysis helps one determine the activities that make up a
system, what data are stored and what data enter and leave
the system.
Parts of decision table & function of
each part in one line.
The four parts of decision table are :1. Condition stub : It displays all the necessary
tests or conditions.
2. Action stub : It lists all the processes involved
in a decision table.
3. Condition Entries : It displays all possible
permutations of Yes and No responses related
to Condition stub.
4. Action Entries : It indicates via dot or X
whether something should happen in a
decision table.
Type of Relationship
• One to One :-A department is headed
by a faculty member
DEPARTMENT
Heade
d by
FACULTY
MEMBER
• One to Many:- A student enrolls for
various courses in a college
STUDENT
• Many to One
• Many to Many
Enrols
COURSE
Difference between ER Modeling and
Object Modeling techniques.
ER Modeling
Object Modeling
It’s goal is normalization and fast Its goal is to model a business
retrieval of data
process using real world objects.
Cannot map real world models as Can map real world model as it
it does not consider/include
includes behaviours
behaviour.
(relationships, calculations and
relations) Offers a dynamic
architecture.
Grouping is possible only on the
basis of entity types.
Flexible grouping possible as
objects can also be grouped on
the basis of behaviour types.
ADVANCED DATABASE
TECHNOLOGIES
• Data Warehouse (DW) : The Data warehouse is a
system for storing and delivering massive quantities of
data. It is a centralized data repository that stores and
provides already transformed and summarized dat,
therefore, making it an appropriate environment for more
efficient DSS and EIS applications.
• Metadata : Metadata is data about data. The information
that describes the model and definition of the source
data elements is called Metadata.
• Data Dictionary : It is a data about data and database
structures i.e. the metadata.
• Data Mining : It refers to the extraction of hidden
predictive information patterns from large databases.
• Object Modeling: The object modeling
refers to building models and performing
activities to deploy a good object-oriented
sytem.
• Object : An object is an identifiable entity
with some characteristics and behaviour.
• Class : A class represents a group of
objects that share common properties and
relationships.
• Data abstraction:- Abstraction refers to
the act of representing essential features
without including the background details
for explanations.
• Encapsulation:-The wrapping up of data
and functions (that operate on the data)
into a single unit is called as
Encapsulation.
• OMT:- OMT is an object building
techniques used to perform OOAD (Object
Oriented Analysis and Design).
Different b/w conceptual data modeling of
and logical data modeling of DDLC
Conceptual data modeling produces a
data model as per client’s observations. It
represents the client’s world-view.
Logical data modeling, on the other hand,
refines the conceptual model by applying
various refinement techniques so that actual
relations schema is ready, which will
eventually be converted and stored in the
database.
UML
UML stands for Unified Modeling Language,
which is an open and industry standard
visual modeling language for object-oriented
systems
Front End and Back End:• Front End:- A front end refers to the client side end
i.e. the end at which request is mad. Some popular
front end software are:–
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Visual Basic (VB)
ASP (Active Server Page)
Visual C++
Power builder
MS-Access
• Back End:-A Back End refers to the server side,
where the client requests are processed. Some
popular back end software are:–
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SQL Server.
Oracle
Sybase
My SQL etc.
Front End & Back End
Figures
Client/Server Computing
Client/server computing represent a model
wherein request are made in one a end i.e
client end and the services are provided at
another end i.e the server end.
Client: - the client is defined as a requested of
services and the server is defined as the
provider of the services. Two of Client:a. Thin client
b. Fat Client
Computing Model
• 2-tier Computing Model :- The 2-tier computing
model consists of a client tier and a database
server tier. Processing tasks and application logic
are shared between the database server and the
client
• 3-tier Computing Model:In a three-tier computing model there exist three
tiers:(i)client tier
(ii)(ii) middle tier and
(iii)(iii) database server tier.
The middle tier consists of application server that
contains the bulk of the application logic
SQL( Structured Query Language)
• First Commercial SQL was released in 1979 by Relational
Software Incorporation (RSI) which is today known as Oracle
Corporation. Thus, Oracle is the pioneer RDBMS that started
using SQL.
• Structured Query Language (SQL) is a language that enables
you to create and operate on relational databases.
• The Original version of SQL was developed by IBM’s San Jose
Research Laboratory (Now Almanden Research Center ). SQL,
originally called “Sequel” was implemented as a part of System
R Project in early 1970s. The “Sequel” name changed to SQL.
• In 1986, the American National Standards Institute (ANSI)
published an SQL standard that was updated again in 1992.
• SQL has clearly established itself as the standard relational
database language.
• SQL is the set of commands that is recognized by nearly all
RDBMSs.
SQL
(Structural
Query
Language)
DDL
(Data
Definition
Language)
1. Create
2. Alter
3. Drop
DML
(Data
Manipulation
Language)
1. Insert
2. Delete
3. Update
DRL
(Data
Retrieval
Language)
1. Select
DCL
( Data
Control
Language)
1. Grant
2. Revoke
1.
2.
3.
4.
TCL
( Transaction
Control
Language)
Commit
Rollback
Savepoint
Set Transaction