Q. What is DATA MINING ?

Ans. Data mining can be defined as "the nontrivial extraction of implicit, previously unknown, and potentially useful information from data". Data mining may also be defined as "the science of extracting useful information from large data sets or databases".

Data mining is the principle of sorting through large amounts of data and picking out relevant information. It is usually used by business intelligence organizations, and financial analysts, but it is increasingly used in the sciences to extract information from the enormous data sets generated by modern experimental and observational methods.

Data mining has been cited as the method by which the U.S. Army unit Able Danger supposedly had identified the September 11, 2001 attacks leader, Mohamed Atta, and three other 9/11 hijackers as possible members of an al Qaeda cell operating in the U.S. more than a year before the attack.






Q. What is data warehousing?

A data warehouse is the main repository of an organization's historical data, its corporate memory. It contains the raw material for management's decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems.

Bill Inmon, an early and influential practitioner, has formally defined a data warehouse in the following terms;

Subject-oriented
The data in the database is organized so that all the data elements relating to the same real-world event or object are linked together;
Time-variant
The changes to the data in the database are tracked and recorded so that reports can be produced showing changes over time;
Non-volatile
Data in the database is never over-written or deleted - once committed, the data is static, read-only, but retained for future reporting; and
Integrated
The database contains data from most or all of an organization's operational applications, and that this data is made consistent.
A data warehouse might be used to find the day of the week on which a company sold the most widgets in May 1992, or how employee sick leave the week before the winter break differed between California and New York from 2001–2005.

While operational systems are optimized for simplicity and speed of modification (see OLTP) through heavy use of database normalization and an entity-relationship model, the data warehouse is optimized for reporting and analysis (online analytical processing, or OLAP). Frequently data in data warehouses are heavily denormalised, summarised or stored in a dimension-based model. This is not always required to achieve acceptable query response times, however.



There are many advantages to using a data warehouse, some of them are:

Data warehouses enhance end-user access to a wide variety of data.
Decision support system users can obtain specified trend reports, e.g. the item with the most sales in a particular area within the last two years.
Data warehouses can be a significant enabler of commercial business applications, particularly customer relationship management (CRM) systems.

2007 QP

Q.1 What are management support systems?

Ans. MANAGEMENT SUPPORT SYSTEMS (MSS)
• When information systems focus on providing information and support for effective decision making by managers, they are called Management Support System.
• MSS was introduced when the concept of MIS originated in the 1960’s.
• MIS became buzzword of almost all attempts to relate computer technology and systems theory to data processing in organizations.
• MIS concept is recognized as vital to efficient and effective information systems in organizations for two reasons:
1. It emphasizes management orientation of information technology in business. A major goal of computer based information systems should be the support of management decision-making, not merely the processing of data generated by business operations.
2. It emphasizes that a system framework should be used for organizing information systems applications. Business applications of information technology viewed as interrelated and integrated computer-based information systems and not as independent data processing jobs.

Several major types of information systems are needed to support a variety of managerial end user responsibilities:
1. Management Information Systems
2. Decision Support Systems
3. Executive Information Systems






Q.2 Explain various types of Decision Support Systems and why do managers need them?

Ans. Decision Support Systems:
• DSS are a natural progression from information reporting systems and transaction processing systems.
• Are interactive, computer based information systems that use decision models and specialized databases to assist the decision making processes of managerial end users.
• Provide managerial end users with information in an interactive session on an adhoc (as needed) basis.
• Provides managers with analytical modeling, simulation, data retrieval, and information presentation capabilities.
• Managers generate the information they need for more unstructured types of decisions in an interactive, simulation-based process.
• When using a decision support system, managers are simulating and exploring possible alternatives and receiving tentative information based on alternative sets of assumptions. So, managerial end users do not have to specify their information needs in advance.
• Decision Support Systems interactively help them find the information they need.







Q.3 Discuss the various problems and issues involved in integration of Decision Support Systems with Expert Systems.

Ans. EXPERT SYSTEMS
• An expert system, also known as a knowledge based system, is a computer program that contains some of the subject-specific knowledge, and contains the knowledge and analytical skills of one or more human experts.
• The most common form of expert systems is a program made up of a set of rules that analyze information about a specific class of problems, as well as providing mathematical analysis of the problem(s), and, depending upon their design, recommend a course of user action in order to implement corrections.
• Expert systems are designed and created to facilitate tasks in the fields of accounting, medicine, process control, financial service, production, human resources, medicine, engineering, the physical sciences etc.
• Expert systems help to diagnose illness, search for minerals, analyze compounds, recommend repairs, and do financial planning.
• Expert systems can support either operations or management activities.
• Most expert systems are developed via specialized software tools called shells. These shells come equipped with an inference mechanism and require knowledge to be entered according to a specified format.

EXPERT SYSTEMS BUILDING TOOLS: DEFINITIONS
An expert system tool, or shell, is a software development environment containing the basic components of expert systems. Associated with a shell is a prescribed method for building applications by configuring and instantiating these components. Some of the generic components of a shell are shown in Figure below. The core components of expert systems are the knowledge base and the reasoning engine.

1. Knowledge base: A store of factual and heuristic knowledge. An ES tool provides one or more knowledge representation schemes for expressing knowledge about the application domain. Some tools use both frames (objects) and IF-THEN rules. In PROLOG the knowledge is represented as logical statements.

2. Reasoning engine: Inference mechanisms for manipulating the symbolic information and knowledge in the knowledge base to form a line of reasoning in solving a problem. The inference mechanism can range from simple backward chaining of IF-THEN rules to case-based reasoning.


3. Knowledge acquisition subsystem: A subsystem to help experts build knowledge bases. Collecting knowledge needed to solve problems and build the knowledge base continues to be the biggest bottleneck in building expert systems.

4. Explanation subsystem: A subsystem that explains the system's actions. The explanation can range from how the final or intermediate solutions were arrived at to justifying the need for additional data.

5. User Interface: The means of communication with the user. The user interface is generally not a part of the ES technology, and was not given much attention in the past.

Integrating GIS and web technologies with expert systems can provide valuable real time spatial decision support. Traditional DSS lack expert knowledge and are mostly PC based software components. The benefits of the traditional DSS can be further leveraged by embedding expert knowledge and implementing the DSS using the web-based technologies. Embedding expert knowledge with the DSS provides intelligent decision support rivaling a human expert, and implementing intelligent DSS over the web provides many advantages, such as anytime anywhere access, no distribution costs, ease of use, centralized data storage.






Q. 4. What is Knowledge Management?

Ans. KNOWLEDGE MANAGEMENT SYSTEMS

Knowledge: is justified belief that increses an entity’s capacity for effective action. Knowledge can also be defined as

i. facts, information, and skills acquired by a person through experience or education; the theoretical or practical understanding of a subject, or
ii. what is known in a particular field or in total; facts and information or
iii. awareness or familiarity gained by experience of a fact or situation.

Informaion vs. Knowledge
- Flow of messages or meaning which may add to, restructure, or change knowledge.
- Information is raw material for production of knowledge.

Knowledge Management
- ('KM') comprises a range of practices used by organisations to identify, create, represent, and distribute knowledge for reuse, awareness and learning.

- Knowledge Management programs are typically tied to organisational objectives and are intended to achieve specific outcomes, such as shared intelligence, improved performance, competitive advantage, or higher levels of innovation.

- The idea of a KM system is to enable employees to have ready access to the organization's based documented of facts, sources of information, and solutions.

- Many organizations are developing KMS to manage organizational learning and business know –how. Many knowledge management systems rely on Internet and intranet Web sites, knowledge bases, and discussion forums as key technologies for gathering, storing, and disseminationg business knowdelge.

- For example, an engineer could know the metallurgical composition of an alloy that reduces sound in gear systems. Sharing this information organization wide can lead to more effective engine design and it could also lead to ideas for new or improved equipment.

A KM system could be any of the following:

1. Document based i.e. any technology that permits creation/management/sharing of formatted documents such as Lotus Notes, web, distributed databases etc.
2. Ontology based: these are similar to document technologies in the sense that a system of terminologies (i.e. ontology) are used to summarize the document e.g. Author, Subj, Organization etc. as in DAML & other XML based ontologies
3. Based on AI technologies which use a customized representation scheme to represent the problem domain.
4. Provide network maps of the organisation showing the flow of communication between entities and individuals
5. Increasingly social computing tools are being deployed to provide a more organic approach to creation of a KM system.

Benefits of KM Systems
1. Sharing of valuable organizational information.
2. Can avoid re-inventing the wheel, reducing redundant work.
3. May reduce training time for new employees
4. Retention of Intellectual Property after the employee leaves if such knowledge can be codified.

Q. 5. Describe the role and various phases of development of knowledge enabled customer relationship management system in an organization.

Identifying the high value customer is a sophisticated knowledge task, as is determining the range of profiles among the current customers. Technology can assist but knowledge management puts the information processing power of technology to effective use. Collaborating with the customers requires a strong grasp of tacit knowledge exchange, and anticipating or predicting new customer needs can be delivered competently using statistical methods with the technology, but can only be done excellently when the dimension of tacit knowledge exchange and collaboration are also deployed. Gathering and analyzing knowledge about the customers is the oldest form of marketing knowledge activity. Technology enhances the collection of information, particularly but not exclusively, activity on the web. While recording consumer click through behavior on websites is now suspect for privacy reasons, in the aggregate it can give strong indications about web usability and broad trends in interest. Similarly the studies by video camera of consumer walking patterns through stores can help determine which layouts are more effective than others.

Q. “The functions of the information systems include the gathering, maintenance and analysis of data concerning internal resources and intelligence about competitors, suppliers, customers, government and other relevant organizations.” In the light of the above statement describe how information system helps MIS?

Ans. MIS is a general name for the academic discipline covering the application of people, technologies, and procedures – collectively, the information system to business problems.
In business the information system supports not only business processes and operations, but also decision making and competitive strategies, which are all fields of MIS.
As an area of study, MIS is sometimes referred to, in a restrictive sense, as information technology management. The sydy of information systems is usually a commerce and business administration discipline. Concentrates on the integration of computer systems with the aims of the organization.
The are of study should not be confused with the computer science which is more theoretical in nature and deals in mainly with software creation. IT service management is a practioner- focused discipline centring on the same general domain.

Investing in information systems can pay off a company in many ways:
1. an investment can support a core competency.
2. it can enhance distribution channel management
3. Such an IT investment can help build brand equity.
4. IT investment can boost production processes. its output level.
6. IT investment can impact mass customization production processes.
7. Leverage IT investment in computer aided design.5. Information systems allow a company flexibility in
8. It can mean expanded e-commerce.
9. Information systems leverage stability.
10. It can improve B to B commerce in the ever growing global economy.