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Monday, July 23, 2012

What is a Data warehouse? What is the purpose of a data warehouse?

A data warehouse can define as a repository  that can be accessed to retrieve information of an organization's electronically stored data, designed to facilitate reporting and analysis.


When we go to the history of data warehouse we can define the concept of data warehousing dates back to the late 1980s .The concept of data warehousing was reviled when IBM researchers Barry Devlin and Paul Murphy developed the business data warehouse. In essence, the data warehousing concept was intended to provide an architectural model for the flow of data from operational systems to decision support environments.


Data warehouse is a subject-oriented, integrated, time-variant, non-volatile collections of data used to support analytical decision making. When we further explore we can identify that data warehouses are physically separated from operational systems, even though the operational systems feed the Warehouse with source data. Anywhere Data warehousing concept was intended to provide an architectural model for the flow of data from operational systems to decision support environments. The concept attempted to address the various problems associated with this flow, mainly the high costs associated with it. We can demonstrates how the data warehouse serves as a facilitator to retrieve data from any source such as independent databases and their external interfaces as follows.


When we go though the data warehouse we can identify following purposes,

Multiple angles:This allows viewing data from multiple angles (dimensions). We can identify this as one of the best aspects of the Data warehouse.

Providing an adaptive and flexible source of information: Data Warehouse has the capabilities to adapt quickly to the changing requirements. So it is really easy to handle the necessary changers when it needed. That’s why we can say that it is adaptive and flexible metherod for the source of information

Establish the foundation for Decision Support: We all know that decisioning process of an organization will involve analysis, data mining, forecasting, decision modeling etc. So by having a common point that allows to provide consistent, quality data with high response time provides the core enabler for making fast and informed decisions.

All systems into one environment: We all know that in enterprise environment which may have many systems of record. The data warehouse allows to aggregate all systems into one environment.

Keeping Analysis/Reporting and Production Separate: Data ware aids to keep analysis/reporting (non-production use data) separate from production data. So this can identify as one of purpose of implementing a data warehouse

Data Consistency and Quality :It is common that organizations are riddled with different types of important systems from which their information comes. Each of these systems may carry the information in different formats and also may be having out of synch information. So by bringing the data from these disparate sources at a common place, one can effectively undertake to bring the uniformity and consistency in data

Operational database

Operational Database can simply define as a database of record, consisting of system specific reference data and event data belonging to a transaction update system which contains enterprise data which are up to date and modifiable.So this is the source of data for the data warehouse. When we further go more detail study about the optional database we can identify that operational database contains detailed data used to run the day to day operations of the business. That's why we can say that it contain data which as up to data as the name implies.
So, operational database, capturing real time data and supplying data for real time computations and other analyzing processes.

There are number of advantages of using an operational database. We can identify those advantages as follows,


  • System-specific reference data and event data belonging to a transaction-update system
  • Contain system control and detailed data used to run the day-to-day operations
  • Data are up to date and data are modifiable
  • Enterprise data

What is Data mining?

Data mining can define as a process of extracting patterns from data. So it is the drawing out of hidden predictive data from huge databases. Data mining derives its name from the similarities between searching for valuable information in a large database.
We can identify data mining is as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage. Because it is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Long process of research and product development Data mining techniques are become results. Data mining has become increasingly common in both the public and private sectors. Organizations use data mining as a tool to survey customer information, reduce fraud and waste, and assist in medical research.
Data mining commonly involving tasks:
When we move for a detail study about the data mining, we can identify that data mining commonly involves four classes of tasks as follows,
Clustering :
It is the task of discovering groups and structures in the data that are in some way or another "similar", without using known structures in the data.
It is the task of generalizing known structure to apply to new data.

This is the attempts to find a function which models the data with the least error.
Association rule learning :

Searches for relationships between variables.

Mixed strategy database design approach

This database design approach uses both the bottom-up and top-down approach intend of following any particular approach for various parts of the data model before finally combining all parts together. So the requirements are portioned according to a top-down approach and part of the schema is designed for each partition according to a bottom-up approach. Then after as the final phase all the schema parts are combined together.

Inside-out database design approach

The inside-out database design approach can define as a special case of a bottom-up approach. This approach starts with the identification of set of major entities. Then after it spreading out to consider other entities, relationships and attributes associated with those first identifies. In this approach attention is focused at a central set of concepts that are most evident and then spreading outward by considering others in the vicinity of existing ones.

Why top-down database design approach is important?

In top-down approach, it helpful to visualize the system. This visualization of the system use to represent the idea behind the particular system and this will really helpful to identify the system and understand the related system. That's why we can say that top down approach is a really good way for the representation.

Why bottom-up database design approach is important?

The bottom-up approach starts with the data and goes on to develop the structure around it. Here the approach can use to avoid the duplicate and redundant data. We all know that if some piece of data is duplicated several places in the database, there is the risk that it is updated in one place but not the other. This will lead for data corruption. In the same time this will aids to prevent such anomalies while ensuring the integrity of data in the database. So we can say that bottom-up database design approach is really important.

Bottom-up database design approach:

When we go through the different approaches available to design a database, we can identify bottom-up database design approach as the other main approach available for database design. In bottom-up database design first defines the required attributes and then groups the attributes to form entities.

So this diagram represent the bottom-up approach database design approach starts at the fundamental level of attributes(or abreactions) that is properties of entities and relationships. Then after we can see that it combines or add to these abreactions which are grouped into relations that represent types of entities and relationship between entities.


We can identify the normalization process as an example for bottom up approach to database design. Here in this process of generalizing entity types into higher-level generalized supper classes is amount example of bottom-up approach. We can further describe by taking a table, we can use the normalization steps to split the one table up to multiple tables


When we go through the data model we can identify different types of advantages. We can summarized the main advantages of this as follows,

  • Prevent anomalies.
  • reduce the redundancies
  • Ensure the integrity

Top-down database design approach

When we go through the different approaches available to design a database, we can identify top-down
design as a one main approach available for database design. When we go through the different approaches available to design a database, we can identify top-down
design as a one main approach available for database design. This approach begins by identifying the different entity types and the definition of each entity's attributes.

Mainly top-down database approach starts with the development of data model or schemas that contains high-level abstractions. This approach helps database designers to get a good overview over the customers business, the business practices, business rules and reporting requirements.


We can say that Entity relationship diagram or model(ERD) is an example of top-down approach and is more suitable for the design of compiled databases. The process of specialization to refine an entity type into subclasses is another example of the top-down database design approach


When we go through the data model we can identify different types of advantages. We can summarized the main advantages of this as follows,

visualization of the system

Aids to identify the system

Aids to represent the idea behind the system

Database development life cycle


Database development life cycle is a part of the software development life cycle. Here in database development life cycle there are number of stages that we can identify. We can present those stages as follows,


Initial database study:


This phase that we identify the requirements that are related to the implementation of database. So here in this phase we determine what is required, what kind of a database is needed for the organization, what is the volume of the data must be handled, how much data is to be stored in the master files etc.


Database design:


In this phase database designers make decision on the database model that is perfectly suited for the organizations requirements. To meet this database designers study the documents prepared by the analysts in the requirements analysis stage and then start developing a system that fulfills the needs.


When we go for the further detail study of the Database design we can identify that it starts with a conceptual data model and produces a specification of a logical schema. However the relational representation is still independent of any specific Database management system (DBMS). So it is another conceptual data model

Implementation and data model:

This is the phase that the database system is implemented. This involves a series of steps leading to operational information system that includes creating database definitions, developing applications, testing the system, developing operational procedures and documentation, training the users and populating the database

Testing and evaluation:


Here in this phase the
aim of testing is to uncover errors in the design and implementation of the database, its structure, constraints and associated user and management support.


This considered involving validation and verification. Without adequate testing users will have little confidence in their data processing.


In this phase database is accessed by the users and application programs, new data is added as well as the existing data is modified and some obsolete data is deleted also database delivers its usefulness as a critical tool in management decision making and help in the smooth and efficient functioning of the organization.

Maintenance and monitoring:

We can identify this phase as one of the ongoing phases in database development life cycle. Database backup and recovery, performance tuning, design modifications, access management and audits, usage monitoring, hardware maintenance and upgradation can identify as major tasks that are carryout during this process.

The documentations produced for each stage of the database development life cycle

When we go through the detail study of the database development life cycle we can identify that throughout the database system development lifecycle the database developer needs to capture facts about the current and or future system.


So we can see that to full this requirement number of documentations are produced for each stage during the database development life cycle. We can summarize the documentations that are implement during each pages as follows,




  • Initial database study
  • Mission statements and objectives of database system
  • Definition of scope and boundry of database application
  • Definition of user views to be supported
  • User and system requiremets specification
  • Database design
  • Conceptual/logical database design
  • ER model(s)
  • Data dictionary
  • Relational schema,
  • Physical database design
  • Implementation and data model
  • DBMS evaluation and recommendations
  • Testing and evaluation
  • Testing strategies used, anlysis of test results
  • Operation
  • User manual
  • Maintenance and monitoring
  • Analysis of performance results
  • Modified user's requirements and systems specifications


Why database management system is important?

Database management systems (DBMS) are normally perform a multitude of functions including providing security, multi-user access while transforms data into information. These database management systems manage (DBMS) data stored and contain programming languages. So we can say that Database management system (DBMS) is the system of computer software that is aimed to provide a managing tool for maintaining the data.

Normally database management systems (DBMS) are used to provide better service to the users. We all know that changes are often necessary to the contents of data stored in any system. Here doing necessary changes are more easily made. Not only that since all access to the database must be through the database management system (DBMS) standards are easier to enforce. Likewise there are lot of advantages of using a database management system (DBMS).That's why we can say that using database management systems are really important.

Database management system

A Database Management System (DBMS) can define as a system software package that aids the use of integrated collection of data records and files known as databases. It allows organizations to place control of database development in the hands of database administrators (DBAs) and other specialists.

As the ajor purpose of a database system we can define as to provide users with an abstract view of the data. These database management systems, generally facilitates the processes of Defining, Constructing and Manipulating of data. It also provides background services including transaction management, disaster recovery and security by defining access rights the data table level. If the user does not have access to a specific table, the particular user is not allowed to access to the particular query that uses data from that table.


When we go through the database management system we can identify different types of advantages. We can summarized the main advantages of this as follows,

  • Redundancies and inconsistencies can be reduced
  • Data is stored and accessed efficiently including the support of very large files and index structures
  • Integrity can be improved and standards can be enforced
  • Let users feel the data is accessed only by him at that time
  • Provides necessary security to protect the data stored and centralize administration


Why entity relationship diagram is important?

This entity relationship diagram drawn when designing a database system. It is normal that, after the systems specification, this diagram is drawn showing the conceptual design of the database. ERD or entity relationship diagram shows the type of information that is to be stored in the system and how these information associate with each other.When creating, the entity relationship diagram this will give a perfect view of all database elements. This visual representation is really easy to understand and in the same time this diagram can be shown and explained to user representatives for confirmation and approval.

ERD (Entity-relationship diagram)

It can define as an abstract and conceptual representation of data. This was first described in the year 1976 by Dr. Peter Chen Properly and it was appeared in a paper in the first issue of the ACM publication, "Transactions on Database Systems". When concern about the Entity-Relationship Approach it consists of an analytical method and consists with modeling technique. In today's world it recognized as one of the most important tools in the data administration tool kit. When we go through the Entity relationship diagram we can identify that, E-R Diagrams use mainly three symbols to represent the relationship among entities.

Entity: A real-world item or concept that exists on its own. Here we can define an entity type as a rectangle containing the type name

Attribute: An Attribute
is a characteristic of an Entity; they are properties used to distinguish one entity instance from another. Attribute is represented by an clipcy.

Relationship: As an association between two entities to which all of the occurrences of those entities must conform which is represented by a diamond



We can summarized the main advantages of this entity relationship diagram can be define as follows,

  • All the major components of the information environment are formally represent
  • The major relationships of data have been formally recognized
  • Aids to maintain good and consistent naming standards
  • Visualize representation

Why database design is important?

In database design it is in consistent form. So when the database is designed only relevant and required data will be stored. Because of that the layout of the table allows the data to be consistent. In the other hand to keep the data consistent this can be handle through implementation of primary keys and unique key constraints.

Also overall performance of the application is also dependent on the design of the database. Not only that, database design improve the store and management of data and its structures. So we can say that database design is so important.

Why data mining is important for the university setting?

Simply data mining refers to extracting or mining knowledge from large amount of data. So data mining is searching, analyzing and sifting through large amounts of data to find relationships, patterns, or any significant statistical correlations. When we go through data mining in a university setting we can identify number of positive impact.

Data mining can use to identify students progress within the university. So this will helpful to identify who are the week students that need to pay more attention. That's' why it is really easy to select the weak students to pay more attentions to help to improve their studies. Not only that data mining can use to identify the requirements of the students as well as the new patters. In the same time this will helpful to allocate resources and staff more effectively while considering the number of students and their requirements. While concerning all these things we can say that data mining is really important for the university setting.

Why data mining is important?


In data mining concept main purpose is to used for analysis of collected information. So here unknown interactions between data are researched in a variety of ways to ascertain critical relationships between subjects and aggregated information. That's why data mining is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, e-commerce, investment trend in stocks & real estates, telecommunications and so on.In global market data mining has great importance in highly competitive business environment. Because it is a good method to manage latest information and used for competition analysis, market research, economical trends, consume behavior, industry researches and so on. While considering all these things we can identify that data mining is really important.

Difference between data warehouse and an operational database

When we go though the data warehouse and operational database we can identify number of differences. We can define those differences as follows,

Operational database

Data warehouse

Stored with a functional or process orientation

Stored with a subject orientation

In operational database data are stored with a functional or process orientation. But when we move to the data warehouse we can identify that data are stored with subject orientation that facilitates multiple views for data and decision making.

Operational database

Data warehouse

Different representation or meanings

Unified view of all data elements with a common definition and representation

Data warehouse concepts it unified view of all data elements with a common definition and representation.In operational database similar data are allowed different representations

Operational database

Data warehouse

Represent current transactions

Historic in natural

Data are historic in nature in data warehouse. Here a dimension is added to facilitate data analysis and time corporations. But if we turn our eye to the operational database we can recognize that in operational database model data represent in current transactions. So there is a big difference in this perspective

Operational database

Data warehouse

Update and delete

Add only periodically from operational system

In datawarehouse data are changed. But here data only added periodical from operational systems. But when we turn our eyes to the operational database perspective we can recongniz that data update and deleted are really common in operational database.

Why data warehouse is important?

We all know that data warehouse is a collection of an organization's data stored in an electronic format which most commonly organized and stored in a structure conducive to high speed analysis and summary reporting. In this new millennium it is a great solution where organizations and other businesses factors can have their applications made that will contribute to their global market success. The applications contain all the information required by analyzing how the industry runs and use it to draw their strategy to keep the particular company or organization on top of the competition as much as possible.

Data warehouse always provide fast, effective reporting without the burden of significant added overhead to the organization's operational databases. So it is really easy as well as it save time. Not only that normally data warehouse is thought of as a database of meta data while data warehouse system include components to load, transform, and extract data, as well as tools used to retrieve, analyze, and report on the data and it improve the standardization of data collected from multiple sources.Also when we go further details study of the data warehouse importness we can identify that processing queries and reports from the data warehouse leaves the databases free to provide the transactional processing for which they were designed. While concerning all these factors we can identify that data warehouse is really important.

Why relational approach to data modeling produces database more flexible to change compare to other hierarchical and network data models?

When we go through the data models we can identify that relational database model is naturally scalable and extensible, providing a flexible structure to meet changing requirements and increasing amounts of data when comparing to other data models.This model permits changes to a database structure to be implemented easily without impacting the data or the rest of the database.So it is really easy for the database analysis to make necessary changers in existing database. That's why we can say that relational databases offer structural flexibility for the applications written for those databases are easier to maintain than similar applications written for hierarchical or network databases. That same structural flexibility enables to retrieve combinations of data that may not have anticipated needing at the time of the database's design.In theoretically there is no limit on the number of rows, columns or tables. But in the real world growth and change are limited by the relational database management system and physical computing hardware, and changes may impact external applications designed for a specific database structure.

Comparison between hierarchical model, network model and relational model

Data models, Data structures, Data manipulation, Data integrity comparison


When we move with the data models such as hierarchical model, network model, relational model we can identify number of difference in terms of data structures, Data manipulation and Data integrity.



Hierarchical model

Network model

Relational model


Data structure

When we go through the structure of

the hierarchical model we can identify that it used a method for storing data in a database that looks like a family tree with one root and a number of branches or subdivisions. That's why we can say that record types are organized in the form of a rooted tree. But in network model we can identify multiple branches emanating from one or more nodes. So some times it is like a like several trees which share branches. In relational model is that of a relation. Relation is a two-dimensional table. So the table can be used to represent some entity information or some relationship between them

Data structure

One to many or one to one relationships

Allowed the network model to support many to many relationships

One to One,
One to many, Many to many relationships

In hierarchical model only one-to-many or one-to-one relationships can be exist. But in network data model makes it possible to map many to many relationships In relational each record can have multiple parents and multiple child records. In effect, it supports many to many relationships

Data structure

Based on parent child relationship

A record can have many parents as well as many children.

Based on relational data structures


In hierarchical model relationship based in terms of parent child. So a child may only have one parent but a parent can have multiple children. But in network data model a record can have many parents as well as many children. Relational data model is based on relational data structures

Data manipulation

Does not provide an independent stand alone query interface

CODASYL (Conference on Data Systems Languages)

Relational databases are what brings many sources into a common query (such as SQL)

In relational database it use powerful operations such as SQL languages or query by example are used to manipulate data stored in the database But in hierarchical data model it does not
provide an independent stand alone query interface while network model uses CODASYL

Data manipulation

retrieve algorithms are complex and asymmetric

Retrieve algorithms are complex and symmetric

Retrieve algorithms are simple and symmetric

In hierarchical data model and network model retrieve algorithms are complex and symmetric But in relational data model retrieve algorithms are simple and symmetric

Data integrity

Cannot insert the information of a child who does not have any parent.

Does not suffer form any insertion anomaly.

Does not suffer from any insert anomaly.

In hierarchical data model we cannot insert the information of a child who does not have any parent. But in network model does not suffer form any insertion anomaly. relational model does not suffer from any insert anomaly

Data integrity

Multiple occurrences of child records which lead to problems of inconsistency during the update operation

Free from update anomalies.

Free form update anomalies

In network model it is free from update anomalies because there is only a single occurrence for each record set.In relational model it also free form update anomalies because it removes the redundancy of data by proper designing through normalization process. But in hierarchical model there are multiple occurrences of child records. which lead to problems of inconsistency during the update operation

Data intergirty

Deletion of parent results in deletion of child records

Free from delete anomalies

Free from delete anomalies

In hierarchical model it is based on parent child relationship and deletion of parent results in deletion of child records .But in network model and in relational model it is free from deletion anomalies. Because information is stored in different tables.

Stages in Decision Making

Stages in a decision making process can simply define as follows chart, This steps are really effective pattern for making decisions and solving problems.

State the Problem

The first step of this decision making is to identify the problem. Because clear understand of the problems is really helpful when come to a particular desecition . Until have a clear understanding of the problem or decision to be made, it is meaningless to proceed. So when we concern about the Capital bank situation also we can identify the loss of customers as a main problem as well as the completion among other banks.

Identify Alternatives

Most of the time we can identify there are number of several feasible alternatives. So that's why it is really important to research and identify the alternatives. In Capital banking also before they come to an decision about online banking system 1 st they needs to identify the problem and then they needs to identify the alternatives.

Evaluate the Alternatives

Identifying the alternatives is not enough. As well as identifying the alternatives, it is really import to evaluate those alternatives. Capital banks also need to identify the alternative and evaluate it to get some idea about the new implementation

Make a decision

After evaluations will, have some good knowledge about what actually going. So it is really easy to come to an decision.

Implement decision 

We all know a decision has no value unless implement. This reminds that Great decisions are only great when they are carried into action and the action achieves the desired result. In capital bank also they needs to come to an decision and they needs to implement their decision.

Risk Analysis & Risk management

Risk analysis is a technique to identify and assess for mitigation of risks at project initiation and during task execution. It is the systematic study of uncertainties and risks encounter in business, engineering, public policy, and many other areas. Risk analysis is really important to determined determined the various impacts and identify the risks which could lead . Risk managers start with risk analysis, then seek to take actions that will mitigate or hedge these risks.


In the same time this approach helps to define preventive measures to reduce the probability of occurrence and identify methods to avert possible negative effects on the effectiveness of the company to compete in this particular market.

             As the advantage of this approach we can define it is clear to all sides, vendor, contractors and purchaser, what the risks are and who has ownership of each one. According to this approach 1st they identify the threats, Secondly to work out the likelihood of the threat being realized and to assess its impact. Thirdly start to look at ways of managing them. Finally once carried out a risk analysis and management exercise, it is worth to carrying out regular reviews

Cash Flow Forecasting

Cash Flow Forecasting is a prediction of the amount of money that will move through an organization. It is also known as cash flow budget or cash flow projection. The cash flow forecast identifies the sources and amounts of cash coming into the business and the destinations and amounts of cash going out over a given period. The purpose of good cash flow management is to provide a business owner with projected figures that were calculated to ensure the survival of a business and to achieve business targets.

An effective cash flow forecast can mean the difference between success and failure of a business. It enables to estimate whether will have sufficient cash to fund debts over a period of time. In the same time aid in projecting and using available funds in ways that best benefit the business. A cash flow forecast is important if paying out more than will receive in a particular period and highlights any potential cash flow crisis. By forecasting the cash flow of the business, it predict peaks and falls within cash flow and it also comes as a help to if ever need to approach a bank concerning finances


    Saves substantial time and money

    Gives control

    Enables forward planning

    Powerful and expandable.

    Motivating targets for everyone to work towards achieving

    Provides a an accurate monthly cash flow forecast

    Able to specify times when business may need additional funding

    Means of measuring performance

    Inconsistencies in performance can be identified, predicted and remedied

    Major new investments can be bedded in and accurately assessed

SWOT analysis

SWOT Analysis method used to evaluate the Strengths, Weaknesses, Opportunities and Threats involved in a project or in a business venture. The technique is credited to Albert Humphrey who led a convention at Stanford University in the year 1960s and 1970s using data from Fortune 500 companies. SWOT Analysis can identify as a powerful technique for understanding strengths and to find Weaknesses. In the same time it is useful to identify the opportunities and Threats that face. We can't say that SWOT analysis is limited to profit seeking organizations. Because it used in decision making situation, when a desired end state has been defined.


 SWOT stands for strengths, weaknesses, opportunities and threats. 


S     = Strengths

W    = Weaknesses

O     = Opportunities

T     = Threats


This helpful to understand an organization's strengths, weaknesses, opportunities and threats. It enables organizations to focus on strengths, minimize weaknesses, address threats and in the same time allows to take the greatest possible advantage of opportunities available.
SWOT analysis can shown as following figure.



In SWOT analysis, We define Strengths and weaknesses as internal factors. Opportunities and threats as external factors. So, it addressed all factors related to the effort both positive and negative. It is an aid for balance and to develop effective strategy.

  • Strengths:

Strengths in the SWOT Analysis are attributes or that are considered to be important to the execution and ultimate success of the project. So it can describe as an attributes of the person or company that are helpful to achieving the objective.

Below are few examples of strengths

  • Good knowledge.
  • Relationship selling
  • Trust
  • History.
  • Service quality
  • Skillful
  • Weaknesses:

Weaknesses can simply define as an attributes of the person or company that are harmful to achieving the objective. Weaknesses prevent the achievement of a successful result to the project. Weaknesses capture the negative aspects internal that detract from the value offer, or place at a competitive disadvantage. The more accurately identify weaknesses, the more valuable the SWOT will be for assessment.

Below are few examples of Weaknesses,

  • Low or no market share.
  • No brand loyalty.
  • Lack of experience.
  • Limited human resources and staff
  • High cost of production
  • Products or service similar to competitors
  • Opportunities:


are external conditions that are helpful to achieving the objective.
Opportunities may be the result of market growth, lifestyle changes, positive market perceptions , resolution of problems associated with current situations while offerring greater value that will create a demand for services.

Below are few examples of Opportunities,

  • A growing market.
  • Increased consumer spending.
  • Selling internationally.
  • Development of new technology
  • Growing trend and customer base
  • Threats: 

Threats can define as an external conditions which could do damage to the objective. Normally threat is a challenge created by an unfavorable trend or development that may lead to deteriorating revenues or profits.

Below are few examples of Threats,

  • Competitors
  • Price increases by suppliers,
  • Governmental regulation,
  • Economic downturns,
  • Devastating media
  • New substitute products emerging


Impact analysis

This was
defined by Bohner and Arnold as identifying the potential consequences of a change, or estimating what needs to be modified to accomplish a change,
When a detailed assessment is undertaken to forecast the characteristics of the main potential impacts. However impact analysis can simply define as the
process of understanding the complete effect of a particular change. So, it determined which the environmental impacts of a process, product or facility are determined while identifying the full consequences of change.
Impact analysis is also known as Change Impact Analysis and Solution Effect Analysis. The intended of Impact analysis is to help and understand the scale of loss which could occur. In the same time this study defines critical business processes and the resources needed to support them. It will cover many issues such as loss of stakeholder confidence, not just direct financial loss, and reputational damage and so on.


Impact analysis stage can broken down into three overlapping phases such as,



Specify the impacts associated with each phase of the project and the activities undertaken



Forecast the nature, magnitude, extent and duration of the main impacts



Determine the significance of residual


In the same time we can identify three types of Impact Analysis Techniques such as,


In Traceability links between requirements, specifications, design elements and tests are captured and Relationships analyzed to determine the scope of an initiating



In Dependency, Linkages between parts, variables, logic, modules etc. are assessed to determine the consequences of an initiating change.


In Experiential,
impact of changes is often determined using expert design knowledge.

Normally in the business field organizations are often required to carry out an impact analysis to determine the potential impact of the proposed changes. This process use to analyzing all business functions and the effects.

In business field we can identify fundamental components of impact analysis should be identifying the following areas,

'Hard' Impact

Financial loss, breach of standards, failure to comply with regulations

'Soft' Impact

Placed on loss of competitive advantage, damage to reputation

The real purpose of a business impact analysis is to identify those systems that when absent would create a danger to the enterprises survival and also to ensure those systems revive the correct priority in the subsequent business continuity plan.

Four stages of the group development


Forming is the beginning. In this stage the group comes together and gets to initially know one another and form as a group. This stage is usually fairly short. Normally it only last for a single meeting at which people are introduced to one another. In this stage part of the group forming process is asking questions. Normally answering for questions like 'What are supposed to be doing', 'what is being asked', 'when does it have to be done by',' Time will be spent', 'collecting information and bonding'. etc. Members of the team focus on being busy with routines, such as team organization, who does what, when to meet, etc. Finally team assembled and tasks agreed

In this stage most of the time member of the team do not know each other well enough to unconditionally trust one another. So team members naturally behave independently with goodwill towards each other with little or no real trustSo we can say main idea behind the forming stage is the team comes together, gets to know each other and begins to work together.


Storming is the stage that the team starts to address the task suggesting ideas. So, different approaches cause ideas to compete. Normally teams are made or broken in this phase. Some people's patience will break early. Because of that there may be conflict between group members when address the task suggesting ideas.

So in this stage, group development can considered as a point where personal relationships form within the group. If a team is weak at this point it's likely to be less effective.


As the team moves out of the storming phase they will enter the norming phase. In this stage the group begins to settle down. Team members understand each other and know how the team operates. Members of the group start to feel that they belong to it. So members begin to share ideas, feelings, give and receive feedback and generally chat about what is going on and what they are doing. 

Member of the team now understand each other better, they are able to ask each other for help, recognizing vital contributions of members and they are able to appreciate each other's skills and experience.


In this stage team is most productive. According to this phase group practices its craft and becomes effective in meeting its objectives. In performing stage everyone knows each other well enough to be able to work together. In the same time trusts each other enough to allow independent activity.

This is the stage where group identity, loyalty and morale. Team has a high level of independence. When something goes wrong team members have the ability to resolved the problems which have been accorded within the team in a positive manner.

They have the strength to make necessary changes to structure. Team members can look after each other.



This is the final phase added by Tuckman to cover the end of the project to break up of the team. Adjourning is the
process of "unforming" the group. This phase is known as "deforming and mourning". Simply this can define as letting go of the group structure and moving on. In this stage, individuals will be proud of having achieved much and glad to have been part of such an enjoyable group. However adjourning is arguably more of an adjunct to the original four stage model rather than an extension. This stage involves the termination of task behaviors and disengagement from relationships.

Why transferable skills must matched to the target audience?

Audience simply can define as the listeners at a performance. In the other hand presentation can define as an activity of formally presenting something. Presentations are considered as a successful and effective way to present an idea. So presentations are used as a formal method for bringing people together to plan, monitor and review its progress. In everyday business presentations are becoming more frequent and more creative.

The delivery of presentation is of the almost importance. When presenting the presentation it needs to be in a well manner. Because if not deliver it in a correct manner, the exact presented idea will not send to the audience. Even thought it had been sent, the message will soon be forgotten. Not only that even a well prepared speech given to the wrong audience can have the same effect as a poorly prepared speech given to the correct audience. They both can fail terribly. In the same time the presentation of a perfect project plan is a failure if the audience do not understand or are not persuaded of its merits.

That's why as well as concerning about the presentation and the speech, we needs to more concern about the target audience. It is important to keep in mind that whole preparation and content of a speech must therefore be geared not to the speaker but to the audience. So for a better presentation we needs to have right speech to the right audience. To build a better presentation and a speed which match the audience we needs to identify the target audience.

nalysis         - Who are they? How many will be there?

nderstanding     - What is their knowledge of the subject?

emographics     - What is their age, sex, educational background?

nterest         - Why are they there? Who asked them to be there?

nvironment     - Where will I stand? Can they all see & hear me?

eeds         - What are their needs? What are your needs as the speaker?

ustomized         - What specific needs do you need to address?

xpectations     - What do they expect to learn or hear from you?

In presenting a presentation transferable skills helpful to,

Reach out to the audience better.

Motivate and inspire to undertaking the tasks which are presenting.

Improve the interaction and success rate exponentially

Captivate the listeners

Improved leaps and bounds that help in getting out of tricky situations well.

Enhances the personal touch and the actual posturing 

Face people either in person or in groups well

Mentally prepares in advance to face the volley of questions posed by the group

Dive the audience feels awe and enthralls them to listen to the presentation in rapt attention.


Below examples shows how transferable skills effect to the target audience and why those transferable skills must matched to the target audience,


Managing time

Managing time is really important. It is true that even if a presentation is great, it can be irritating for the audience if the speaker does not keep track of time.


The presenter must concentrate not only upon the facts being presented but upon the style, pace, tone and ultimately tactics which should be use. This will helpful to present the idea more trickily.


All speeches should have a definite structure or format. If the presenters don't present the thoughts into a structured manner, the audience will not be able to follow them.

Setting goals

Setting goals also really important part, when going to do a presentation. By setting goals it is really easy to meet to the target aim. This will helpful to give the exact message at the point to the audience and make the message understood and remembered.



When doing a presentation the presenter needs to be more understandable. The presentation needs to use strategies and skills according to the target audients. In the same time the speech also needs be tailored according to the audience. This reminds the quote "Think like a wise man, but communicate in the language of the people". Not only making the presentation, while presenting the presentation, the presenter needs to be more understandable. He or she needs to understand the audios ideas and comments too.


Speaking effectively & Writing concisely

Needs to have an ability to communicate orally more effectively. In the same time better writing skills. How far skilled, the facts that are presented needs to more simple to understand the audience. In the same time, the ideas which are presented needs to be fruitful, simple, well grammar and effective.

Solving problems

The problems and questions that are occurred needs to be solve. For that apply, logic or reasoning to review information, identify problems, causes, evaluate options and select the best solution. For a presenter these skills are really helpful to carry out a better presentation with his or her audience.

Take the attention

When doing a presentation it is really important to take the attention of audience. Here the skill is to take attention of audience long enough to make the point.


Self management includes goals and strategies performance, time management , balance, meeting challenges, meet work and personal commitments in all areas of your life etc. For a better presentation self management is really important form beginning to the end. Because it affect at every movement.


When doing a presentation you need to have the strengths, skills and confidence to put these across the idea to the audience.