The structure of the Decision Support System

The Decision Support System is mainly composed of the following four components –
1. The database and the management of the database.
2. The modelbase and the management of the modelbase.
3. The hardware.
4. The user system interface.

Different components of the Decision Support System
1. Dialogue management
a. Consists of the three sub systems; namely the user interface, the dialogue control, the request translator.
b. The user interface sub system controls the physical user interface.
c. It also manages the appearance of the screen and also accepts the input from the user and then displays the results.
d. The user interface sub system is also responsible for checking the user commands for the correct syntax.
e. The dialogue control sub system is responsible for the maintenance of the processing context with the user.
f. The request translator helps in the translation of the user command into the actions for the model management or the data management components into such a pattern that can be easily understood by the user.

2. Model management
a. The command processor delivers those commands from the dialogue management components to either the model base management system or the mode execution system after receiving the commands from the dialogue management components.

3. Database management
a. Helps in the storage of the database.
b. Also helps in the manipulation of the database.
c. Works under the guidance of the either the model management component or the dialogue management component.
d. Helps in the maintenance of the interface with the data sources that are generally external to the Decision Support System.

Comparison between the Management Information System and the Decision Support System

Characteristics wanted in the Decision Support System
1. Must aid the decision maker in the decision making.

2. Should be able to address the semi/un-structured decision making situations.

3. Should be able to support the decision makers at some of the tactical or the strategic levels.

4. Should be able to create some of the general purpose models, stimulation capabilities and the other analytical tools available to the decision maker.

5. Should enable the users to make use of the Decision Support System without any type of help from the management information system or the technical professionals.

6. Should be able to fulfill the requirements of the information for any type of the decision environment.

7. Must provide the mechanism for carrying on the rapid response to a decision maker’s request for some particular information.

8. Must possess the ability to interface with the corporate database.

9. Should be flexible enough to make it suitable for the various management styles.

10. Should facilitate the much needed communication between the different levels of the decision making.

11. Must have an inbuilt flexibility.

12. Must possess the ability to evolve as the user sophistication grows.

13. Must be able to make use of the various types of the interactive methods that are better for the use.

Factors determining the results in the Decision Support System
1. User training
2. User exercise
3. Involvement
4. Length of the use
5. Top management support
6. Familiarity
7. Orientation towards the top management
8. Novelty of the application
9. Return on the investment

Introduction
In the 1960s, there was a very wide use of the various forms of the information systems but as the time passed and with the coming up of the 1970s, instead of these information systems – a special type of the information systems, quite different from then used information systems came into the limelight. These were very much different from the then used information systems and mainly involved spending less resources, including both of the human as well as the financial.

These new information systems were very much interactive in the nature compared to the earlier used information systems and also played a very critical role in some of the specific enduser utilization of the data and the models in order to discuss and divide – not solve – semi structured and the unstructured problems. These systems at that point of the time were also referred to as the decision support systems.

The decision support systems can be defined as the interactive information systems, which are very much dependent on the integrated set of the user friendly hardware and the software tools, mainly in order to produce the information and then to present the information that is mainly targeted for providing the much needed support to the management in the process of the decision making. The decision support systems play a very defining role in the management decision making with the help of the combination of the data, sophisticated analytical models and the user friendly software into a single powerful system. With the help of this combination, semi structured and the unstructured decision making can be very easily supported to a great extent.

The decision support systems are always under the control of the user, starting from the early inception to the final implementation and the daily use. The decision support systems also have a great role in the closing of the information gap that helps the managers in making the improvement in the quality of their decisions.

The decision support systems involves a particular class of the systems which are used for providing the much needed support to the process of the decision making, but a very important point to be kept in mind here is that the decision support systems does not always give a decision itself.
With the help of the decision support systems the various decisions can be validated with the help of the sensitivity analysis conduction on the different parameters of the problem.

Components of the Decision Support Systems
1. The data base:
a. Is a collection of the current or the historical data from a number of the applications or the groups.
b. Very well organized.
c. Provides very easy access for a large variety of the applications needed.
d. Data integrity is to be maintained in a very efficient way.
e. Decision Support System uses data that have been extracted from the relevant databases – both the internal and the external – and then stored especially for the Decision Support System.

2. The Model – base:
a. A model represents an abstract representation.
b. Illustrates the different components or the relationships of a phenomenon.
c. Can be a physical model, a mathematical model or the verbal model.
d. Types of the models can be categorized as the follows –

A. Behavioral Model –
I. Focuses on studying and understanding the different behavior/trends amongst the variables.
II. Examples of such a model can be trend analysis, co-relation, regression etc.

B. Management Science Model –
I. Based upon the principles of the management, the management accounting and the econometrics.
II. Examples of such a model can include budgetary systems, cost accounting, capital budgeting, inventory management etc.

C. Operations Research Model –
I. Based on the different mathematical formulae.
II. Represent the real life problems depending on the various variables and the parameters expressed in the algebraic equations form.
III. Examples of such a model can be linear programming, ABC analysis, mathematical programming techniques, material requirement planning.

3. The Decision Support System software system –
a. Allows interaction between the users of the system and the Decision Support System data – base and the model – base.
b. Helps in the creation, storage and the retrieval of the models in the model – base.
c. Integrates them with the data in the Decision Support System data – base.
d. Provides a user interface.

Introduction
Data mining can be defined as a tool, helping automatically in the discovery of the various patterns and the relationships in a data warehouse. With the help of the data mining, managers are able to find the various relations between the elements of the business and the find out concepts of the business. Hence, it can be said that data mining extracts trends and rules from data warehouse helping in the evaluation of the business strategies ultimately leading to the improvement in the various business operations.

Data mining very commonly is known as the knowledge discovery database and the various important results that it helps in achieving can be summed up as follows –
a. Discovery of the new associations.
b. Deviation detection.
c. Event clustering.
d. Pattern recognization.
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