The characteristics of an information system are:

• The Organisation of data into information:

  For data to be made meaningful it must have a purpose. The purpose of the stored data should reflect the purpose and type of the information system. Data needs to be processed and organised before it becomes information. Organising the data will most likely involve the processes of sorting and filtering (classifying) before it can be analysed and stored for later retrieval. Data dictionaries are used to help organise the data.

• Ability to Analyse the Information:

• Once the data has become information it needs to be analysed to make the most of the information stored. Analysis of databases is done through the tools of queries and reports.

 

The Different Types and purposes (Functions) of an Information System are:

 

Processing Transactions:

A transaction processing system (tps) collects, stores, modifies and retrieves the transactions of an organization. Examples of such systems are automatic telling machines (ATMs), electronic funds transfer at point of sale (EFTPOS – also referred to as POS). There are two types of transaction of processing:

 

• Batch processing: where all of the transactions are collected and processed as one group or batch at a later stage.
• Real-time processing:where the transaction is processed immediately.

Provide Users with Information About an Organisation:

This information system provides information to managers about the performance of their organisation. It may involve information about payroll, an inventory, stock list or budgets and would require the printing of information in the form of reports normally based on queries. Examples of this kind of system are management information systems (MIS) and executive information systems (EIS).

 

Help Decision-making:

 This type of system is also referred to as a decision support system (DSS). A decision support system will assist people to make decisions by providing tools to analyse the information stored in a system. A DSS will provide a mathematical model of the variables affecting the decision and then point directions for actions that should be taken. One such example is the system that used by stockbrokers, which chart fluctuations in price and then make buy or sell recommendations dependant upon the parameters predefined by the stockbroker. Many DSS will allow managers to ask “what if” style questions and then see what would happen. This is particularly useful when the variables are limited and predictions can be safely based on what is known. A DSS is only as accurate as the mathematical model used.

 

Another kind of DSS is an expert system. Expert systems are designed to help make decisions that would involve someone highly qualified an experienced in that field. An example of an expert system is one used by doctors to help diagnose patients or prescribe drugs.

 

Manage Information used Within an Organisation:

This system is designed to provide an efficient way of dealing with information within an office environment. Another name for this an office automation system. This will include word processors, spreadsheets, databases and email. An example of an office automation system is Microsoft Office.

 

Examples of Database Information Systems

Most Information systems store data in a database and are referred to as Database management Systems. Examples referred to in the syllabus include:

1. A school database holding information on teachers, subjects, classrooms and students
2. The Roads and Traffic authority holding information on automobiles and holders of driver’s licences

3. Video stores holding information on borrowers and videos.

Related Topics: DBMS, The 5 Types of Information Systems, Expert Systems, TPS, DSS, ES, MIS, OAS, Characteristics, computerised methods, non-computerised methods, flat file databases, relational databases, data modelling, URLs, storyboards, searching, HTML, backups, security methods, encryption, firewalls, virus' and virus scanners, passwords and security levels, social and ethical issues, data accuracy, data integrity, data validation, data bias, data reliability, privacy, ownership and control of data, access to data, data warehousing, data mining, freedom of information, acknowledgement of data sources, issues related to new trends, sequential access, direct access, distributed databases, storage media, querying, operators, wildcards, sorting, SQL, biometrics and ethical issues, face recognition , information systems trivia