Ques. 1 What is difference between MIS and DSS? What are the different types of DSS?Ans. Amanagement information system(MIS) provides information that organizations require to manage themselves efficiently and effectively.Managementinformation systemsare typically computer systems used for managing. The five primary components : 1.)Hardware2.)Software 3.)Data (information for decision making)4.) Procedures (design ,development and documentation), and 5.) People (individuals, groups, or organizations).Managementinformation systems are distinct from otherinformation systemsbecause they are used to analyze and facilitate strategic and operational activities.ADecision Support System(DSS) is a computer-basedinformation system that supports business or organizational decision-makingactivities. DSSs serve the management, operations, and planning levels of an organization (usually mid and higher management) and help to make decisions, which may be rapidly changing and not easily specified in advance (Unstructured and Semi-Structured decision problems). Decision support systems can be either fully computerized, human or a combination of both.Difference between MIS and DSS:S.NO. MIS DSS

1.The main focus is on the structured tasks and the routine decisions.Focus is mainly on the semi / un-structured tasks, which demand the managerial judgment.

2.Identifies the information requirement.Develops certain tools for using in the decision process.

3.Data storage is of great importanceThe main emphasis is on the data manipulation.

4.Delivers system depending on the frozen requirements.Current data can be used in the Decision Support System.

5.Only the in direct access to the data by the managers is provided.Managers enjoy direct access to the data.

6.Very much dependent on the computer expert.Depends on the managerial judgment.

7.Access to the data possibly requiring a wait for the managers turn.Waiting is not at all required.

8.MIS manager may not completely understand the nature of the decision.Manager possesses the knowledge about the nature of the decision and the decision making environment.

9.Main stress is on the efficiency.Main emphasis is laid on the effectiveness.

Different types of DSS There are a number of Decision Support Systems. These can be categorized into five types: Communication-driven DSSMost communications-driven DSSs are targetted at internal teams, including partners. Its purpose are to help conduct a meeting, or for users to collaborate. The most common technology used to deploy the DSS is a web or client server. Examples: chats and instant messaging software, online collaboration and net-meeting systems. Data-driven DSSMost data-driven DSSs are targeted at managers, staff and also product/service suppliers. It is used to query a database or data warehouse to seek specific answers for specific purposes. It is deployed via a main frame system, client/server link, or via the web. Examples: computer-based databases that have a query system to check (including the incorporation of data to add value to existing databases. Document-driven DSSDocument-driven DSSs are more common, targeted at a broad base of user groups. The purpose of such a DSS is to search web pages and find documents on a specific set of keywords or search terms. The usual technology used to set up such DSSs are via the web or a client/server system. Knowledge-driven DSS:Knowledge-driven DSSs or 'knowledgebase' are they are known, are a catch-all category covering a broad range of systems covering users within the organization setting it up, but may also include others interacting with the organization - for example, consumers of a business. It is essentially used to provide management advice or to choose products/services. The typical deployment technology used to set up such systems could be slient/server systems, the web, or software running on stand-alone PCs.

Model-driven DSSModel-driven DSSs are complex systems that help analyse decisions or choose between different options. These are used by managers and staff members of a business, or people who interact with the organization, for a number of purposes depending on how the model is set up - scheduling, decision analyses etc. These DSSs can be deployed via software/hardware in stand-alone PCs, client/server systems, or the web.

Accounting Systems decision support systemsThese systems are not necessarily required for decision making but they are desirable to keep track of the major aspects of the business or a contents of these systems is more data processing leading to formal reporting ,with exceptions, if Necessary. These systems account items such as cash, inventory, personnel and so on and relate it to various norms and rules.eg : Charted Accountants use accounts decision software to calculate TAX Saving. Ques. 2 Differentiate between OLAP and OLTP?Ans. We can divide IT systems into transactional (OLTP) and analytical (OLAP). In general we can assume thatOLTPsystemsprovide source data todatawarehouses, whereas OLAP systems help to analyze it.

-OLTP (On-line Transaction Processing)is characterized by a large number of short on-line transactions (INSERT, UPDATE, DELETE). The main emphasis for OLTP systems is put on very fast query processing, maintaining data integrity in multi-access environments and an effectiveness measured by number of transactions per second. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF).

-OLAP (On-line Analytical Processing)is characterized by relatively low volume of transactions. Queries are often very complex and involve aggregations. For OLAP systems a response time is an effectiveness measure. OLAP applications are widely used by Data Mining techniques. In OLAP database there is aggregated,historicaldata, stored in multi-dimensional schemas (usually star schema).

The following table summarizes the major differences between OLTP and OLAP system design.

OLTP SystemOnlineTransactionProcessing(Operational System)OLAP SystemOnline Analytical Processing(Data Warehouse)

Source of dataOperational data; OLTPs are the original source of the data.Consolidation data; OLAP data comes from the various OLTP Databases

Purpose of dataTo control and run fundamental business tasksTo help with planning, problem solving, anddecisionsupport

What the dataReveals a snapshot of ongoing business processesMulti-dimensional views of various kinds of business activities

Inserts and UpdatesShort and fast inserts and updates initiated by end usersPeriodic long-running batch jobs refresh the data

QueriesRelatively standardized and simple queries Returning relatively few recordsOften complex queries involving aggregations

Processing SpeedTypically very fastDepends on the amount of data involved; batchdatarefreshesand complex queries may take many hours; query speed can be improved by creating indexes

Space RequirementsCan be relatively small if historical data is archivedLarger due to the existence of aggregation structures and history data; requires more indexes than OLTP

DatabaseDesignHighly normalized with many tablesTypically de-normalized with fewer tables; use of star and/or snowflake schemas

Backup and RecoveryBackup religiously; operational data is critical to run the business, data loss is likely to entail significant monetary loss and legal liabilityInstead of regular backups, some environments may consider simply reloading the OLTP data as a recovery method

Ques. 3 Explain the Simons model of Decision making? Differentiate between structure , semi structure and unstructured decision making?Ans. Simons model of Decision making Herbert A. Simon developed a model of decision making. The model consisted of three steps, intelligence, design, and choice. In the intelligence phase, the problem is identified, and information is collected concerning the problem. This can be a long process, as the decision to be made comes from the information. The design phase develops several possible solutions for the problem. Finally, the choice phase chooses the solution.

The Intelligence PhaseThe intelligence phase consists of finding, identifying, and formulating the problem or situation that calls for a decision. This has been calleddeciding what to decide. The intelligence stage may involve, for example, comparing the current status of a project or process with its plan. The end result of the intelligence phase is a decision statement.The name of this phase, intelligence, can be confusing. Intelligence as we usually use the term informally, is talking about decision making, it is what we use after we know a decision must be made. Simon borrowed the term from its military meaning, which involves the gathering of information without necessarily knowing what it will lead to in terms of decisions to be made. In business decision making, we must often collect a great deal of information before we realize that a decision is called for.The Design PhaseThe design phase is where we develop alternatives. This phase may involve a great deal of research into the available options. During the design phase we should also state our objectives for the decision we are to make.The Choice PhaseIn the choice phase, we evaluate the alternatives that we developed in the design phase and choose one of them. The end product of this phase is a decision that we can carry out. Structured, semi structured and unstructured decisions Structured DecisionsMany analysts categorize decisions according to the degree of structure involved in the decision-making activity. Business analysts describe a structured decision as one in which all three components of a decisionthe data, process, and evaluationare determined. Since structured decisions are made on a regular basis in business environments, it makes sense to place a comparatively rigid framework around the decision and the people making it.Structured decision support systems may simply use a checklist or form to ensure that all necessary data are collected and that the decision making process is not skewed by the absence of data. If the choice is also to support the procedural or process component of the decision, then it is quite possible to develop a program either as part of the checklist or form. In fact, it is also possible and desirable to develop computer programs that collect and combine the data, thus giving the process a high degree of consistency or structure. When there is a desire to make a decision more structured, the support system for that decision is designed to ensure consistency. Many firms that hire individuals without a great deal of experience provide them with detailed guidelines on their decision making activities and support them by giving them little flexibility. One interesting consequence of making a decision more structured is that the liability for inappropriate decisions is shifted from individual decision makers to the larger company or organization.Unstructured DecisionsAt the other end of the continuum are unstructured decisions. While these have the same components as structured onesdata, process, and evaluationthere is little agreement on their nature. With unstructured decisions, for example, each decision maker may use different data and processes to reach a conclusion. In addition, because of the nature of the decision there may only a limited number of people within the organization qualified to evaluate the decision.Generally, unstructured decisions are made in instances in which all elements of the business environmentcustomer expectations, competitor response, cost of securing raw materials, etc.are not completely understood (new product and marketing strategy decisions commonly fit into this category). Unstructured decision systems typically focus on the individual who or the team that will make the decision. These decision makers are usually entrusted with decisions that are unstructured because of their experience or expertise; it is their individual ability that is of value. One approach to support systems in this area is to construct a program that simulates the process used by a particular individual. In essence, these systemscommonly referred to as "expert systems"prompt the user with a series of questions regarding a decision situation.

Semi-Structured DecisionsIn the middle of the continuum are semi-structured decisionswhere most of what are considered to be true decision support systems are focused. Decisions of this type are characterized as having some agreement on the data, process, and/or evaluation to be used, but are also typified by efforts to retain some level of human judgment in the decision making process. An initial step in analyzing which support system is required is to understand where the limitations of the decision maker may be manifested (i.e., the data acquisition portion, the process component, or the evaluation of outcomes).Grappling with the latter two types of decisionsunstructured and semi-structuredcan be particularly problematic for small businesses, which often have limited technological or work force resources. As Gupta and Harris indicated, "many decision situations faced by executives in small business are one-of-a-kind, one-shot occurrences requiring specifically tailored solution approaches without the benefit of any previously available rules or procedures. This unstructured or semi-structured nature of these decisions situations aggravates the problem of limited resources and staff expertise available to a small business executive to analyze important decisions appropriately. Faced with this difficulty, an executive in a small business must seek tools and techniques that do not demand too much of his time and resources and are useful to make his life easier." Subsequently, small businesses have increasingly turned to DSS to provide them with assistance in business guidance and management.

Ques. 4 What are the different knowledge sharing techniques? What is the difference between data, information, knowledge and wisdom?Ans. PEER ASSIST:Peer Assist is a method of cooperation, based on dialogue and mutual respect among peers. Peer Assist involves a meeting organized by a work team who are starting up a new project (the hosts). The hosts call on another group who already has experience with a similar project. They introduce the background and data of their project and their capabilities. They then express their specific needs .Once the situation is explained, both teams work together to identify possible solutions to the problem.AFTER ACTION REVIEWWhat was supposed to happen? What actually happened? What is the difference? What went well? What could have gone better? What lessons can we learn? CASE STUDYA case study is a written examination of a project, or important part of a project. It has a clear structure that brings out key qualitative and quantitative information from the project. Case studies are often published with a broad audience in mind, so it is useful to bring the most useful and transferable information to the fore. KNOWLEDGE BANKS(WIKIPEDIA)Knowledge Banks are online services and resources which hold information, learning and support: giving you the power to improve your council. They are typically used to showcase the work of an organisation and provide signposts to documents, articles and toolkits.Examples of knowledge banks include: IDeA Knowledge (www.idea.gov.uk), see belowImprovement Network (www.improvementnetwork.gov.uk) KNOWLEDGE CAF A knowledge caf brings people together to have open, creative conversation on topics of mutual interest. It can be organised in a meeting or workshop format, but the emphasis should be on flowing dialogue that allows people to share ideas and learn from each other. It encourages people to explore issues that require discussion in order to build a consensus around an issue.STORY TELLINGPeople have told stories for thousands of years. Even today, stories are part of our daily lives. Stories have recently been rediscovered as a way to transfer knowledge. Stories allow us to describe employee relations or activities in a formal or informal way. The aim is to transmit tacit knowledge that an organization can use. Stories are a simple and accessible way to communicate complex ideas, key messages and lessons learn.MENTORINGPeople have told stories for thousands of years. Even today, stories are part of our daily lives. Stories have recently been rediscovered as a way to transfer knowledge. Stories allow us to describe employee relations or activities in a formal or informal way. The aim is to transmit tacit knowledge that an organization can use. Stories are a simple and accessible way to communicate complex ideas, key messages and lessons learn.COACHINGCoaching is not mentoring. In mentoring, employees are guided by the advice and experience of senior counterparts who take them under their wing. Coaching specifically aims to develop new qualifications and skills in an employee. It aims to improve that persons learning and job performance, so that he/she can then reach organizational goals. The coach does not convey his or her personal vision to the employee. Coaching focuses solely on the employee predefined needs as these relate directly to his/her job; however, this relationship does not necessarily mean that the person reports to the coach. Coaching aims to develop abilities to meet targeted goals in a given work situation.FORUMS AND MEETINGSSmall meetings, discussion groups and large forums can all serve as opportunities for sharing knowledge and learning. But, for this to happen, they have to be organized with learning in mind. The process of the meeting , discussion or forum has to be well planned in advance. By forums and meetings, we are referring to everything from a large conference or congress, to round-table discussions that happen on their own or inside a large conference, to armchair presentations or panel presentations, and any type of staff or regular meeting that brings people together. Meetings and forums can be useful learning and knowledge sharing opportunities when:

WORKSHOPS, TRAINING AND SEMINARSIn traditional courses, people listen to the presenter without interrupting. More and more, this approach is giving way to a much more dynamic and stimulating group learning process. This may involve a workshop, training session or seminar. The trend in learning activities is now for people to interact with their peers. People share what they know. People discuss things. People benefit from each others views and experiences.KNOWLEDGE FAIRGot a lot of information to share with a whole lot of people? Think an interactive presentation would be the ideal way to share your knowledge of a specific subject? Then it may be useful to organize knowledge fair. Knowledge fair is designed to present information on a chosen theme. You can use several technical means to present your information to the target group. They include showcases, panels, scale models and kiosks. You can also have all kinds of demonstrations and presenters.

DataData is a fact that alone is not significant, as is doesnt relate to other data. Data may answer a very basicwhatquestion; such as a glossary definition, directory entry, or code listing. However, a definition or code may require knowledge, if the definition or code is complex.InformationInformation is data that is related and is therefore in context. It can then be transformed into a Process or Procedure, making it useful. Information is data that relateswho,what,whereandwhento each other, providing a baseline for a Process (i.e. control point, cycle time) or a Procedure (i.e. date, code, screen description).While information may become input for a Process or Procedure, the level of understanding may limit that Process or Procedure to an individual or department level. Enterprise and more complex Processes and Procedures require Knowledge.KnowledgeKnowledge is the application of information. Knowledge addresseshowandwhy,in addition towho,what,whereandwhen. The knowledge links all the information together to produce a comprehensive Policy, Process or Procedure.Knowledge allows management to gain an accurate and complete picture of the enterprise Policies, Processes, and Procedures. The Policies, Processes, and Procedures become transformed into an enterprise asset.WisdomWisdom is complete understanding of the effects and outcomes of Knowledge. Wisdom addresseshowandwhy,in addition towho,what,whereandwhenat the Enterprise level. Enterprise Policies, Processes, and Procedures must be at this understanding level to be considered permanent, otherwise the Policy and Process may be considered Conditional.Having clear, concise, complete, and correct Policies, Processes, and Procedures, an enterprise may now assess best practices and compliance issues. Wisdom allows for Policies, Processes, and Procedures to be modified so they reflect the strategic vision, functional alignment, best practices and operational objectives of the enterprise. Management is able to standardize Policies, Processes, and Procedures across enterprise locations, business units and departments.Policies, Processes, and Procedures become a tool for others within the enterprise for remodeling and initiatives; in that they reflect the As-Is guidelines and functions of the enterprise. They can also be referred to as a map to the organization.

Ques. 5 What are different data types in SQL? Also explain what are the different checks and constraints applied on DBMS?Ans.. In SQL Server, each column, local variable, expression, and parameter has a related data type. A data type is an attribute that specifies the type of data that the object can hold: integer data, character data, monetary data, date and time data, binary strings, and so on.SQL Server supplies a set of system data types that define all the types of data that can be used with SQL Server. You can also define your own data types in Transact-SQL or the Microsoft.NET Framework. Alias data types are based on the system-supplied data types. For more information about alias data types, seeCREATE TYPE (Transact-SQL). User-defined types obtain their characteristics from the methods and operators of a class that you create by using one of the programming languages support by the .NET Framework.When two expressions that have different data types, collations, precision, scale, or length are combined by an operator, the characteristics of result are determined by the following: The data type of the result is determined by applying the rules of data type precedence to the data types of the input expressions. The collation of the result is determined by the rules of collation precedence when the result data type ischar,varchar,text,nchar,nvarchar, orntext. The precision, scale, and length of the result depend on the precision, scale, and length of the input expressions. Explicit data type references are made in SQL statements in the creation of domains and base tables and in the alteration of table definitions.The permissible data types and their ranges are:Data typeDescriptionRange

CHARACTER(n)Character string, fixed length n. See1n15000

CHARACTER VARYING(n) orVARCHAR(n)Variable length character string, maximum length n.1n15000

BINARY(n)Fixed length binary string, maximum length n.1n15000

BINARY VARYING(n) orVARBINARY(n)Variable length binary string, maximum length n.1n15000

INTEGER(p)Integer numerical, precision p.1p45

SMALLINTInteger numerical precision 5.-32768 through 32767

INTEGERInteger numerical, precision 10.-2,147,483,648 through 2,147,483,647

BIGINTInteger numerical, precision 19.-9,223,372,036,854,775,808 through 9,223,372,036,854,775,807

DECIMAL(p, s)Exact numerical,precision p, scale s.1p450sp

NUMERIC(p, s)Exact numerical,precision p, scale s.(Same as DECIMAL - see below).1p450sp

FLOAT(p)Approximate numerical,mantissa precision p.1p45Zero or absolute value10-999to 10+999

REALApproximate numericalmantissa precision 7.Zero or absolute value10-38to 10+38

FLOATApproximate numericalmantissa precision 16.Zero or absolute value10-308to 10+308

DOUBLE PRECISIONApproximate numericalmantissa precision 16.Zero or absolute value10-308to 10+308

DATETIMETIMESTAMPComposed of a number of integer fields, represents an absolute point in time, depending on sub-type.

INTERVALComposed of a number of integer fields, represents a period of time, depending on the type of interval.

Different checks and constraints applied on DBMS :1.NOT NULL- Indicates that a column cannot store NULL valueEg: Create table student ( Rollno varchar(10) primary ,Name Varchar(10), Gender Varchar(2) Noy Null);_________________________________________________________________UNIQUE- Ensures that each row for a column must have a unique valueCREATE TABLE PERSON(PERSON_ID VARCHAR(10) PRIMARY KEY,NAME VARCHAR(10) NOT NULL,DRIVINGLICENSE NUMBER(10) UNIQUE NOT NULL,AGE NUMBER(5) NOT NULL);_________________________________________________________________________PRIMARY KEY- A combination of a NOT NULL and UNIQUE. Ensures that a column (or combination of two or more columns) have an unique identity which helps to find a particular record in a table more easily and quickly.Create table student ( Rollno varchar(10) primary ,Name Varchar(10), Gender Varchar(2) NoT Null);_________________________________________________________________FOREIGN KEY- Ensure the referential integrity of the data in one table to match values in another table.Create table course( Courseid Varchar(10) Primary key, Title Varchar(10));

Create table student ( Rollno varchar(10) primary ,Name Varchar(10), Gender Varchar(2) Noy Null, Courseid varchar(10) Foreignkey references course(courseid));_________________________________________________________________________CHECK- Ensures that the value in a column meets a specific conditionEg: Create table student ( Rollno varchar(10) primary ,Name Varchar(10), Gender Varchar(2) Noy Null ,marks number(10) check( marks