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Information Systems Development Process

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Oliver Lines

BABS 2 - Option

Managing Information Systems In Organisations

RECENT ADVANCES IN SYSTEMS DEVELOPMENT WILL RADICALLY

CHANGE THE INFORMATION SYSTEMS DEVELOPMENT PROCESS

INTRODUCTION

In recent years, there has been an abundance of new technologies in the information systems field. These new technologies have altered the very development process itself. Information systems have gone from being a series of one level databases to three dimensional reality, virtual reality, and multimedia systems. In the early days of information systems, the demands were for data, with no real function of artificial intelligence. However, as the 21st century approaches, business has taken on an entirely different function, and the need for individual information systems has grown immensely. This demand for information technology is in all areas of business: corporations, law, medicine, science and even small business. In addition, the worldwide web and the Internet have added an additional factor of communications. Most information systems in use today require at the very least, a measure of Internet capability.

In order to understand the changes in these development processes, the history of databases should be analyzed.

BACKGROUND

Database Management Systems actually began in the 1950s, with what is known as the first generation, also known as file systems on tape. The major task of any computer in those days was to process data under the control of a program. This primarily meant calculating, counting and simple tasks. Second generation databases, file systems on disk, allowed use of computers in dialogue mode as well as batch mode. The development of magnetic disks allowed for more sophisticated file systems, making multiple access possible. These first two generations of DBMS were characterized by the availability of file systems only; strictly speaking these were the forerunners of database systems, the foundations. An important component of these database systems were the static association of certain data sets (files) with individual programs that would concentrate on these. There were high redundancy problems between files; inconsistencies when one program made changes that are not made in all programs; inflexibility against changes in applications; low productivity by programmers since program maintenance was expensive; and the problem of adopting and maintaining standards for coding and data formats.

The third generation, pre-relational databases, started in the 1960s and continued into the 1970s. This generation is characterized by the introduction of a distinction between logical and physical information, along with a parallel need to manage large collections of data. Data models were used for the first time to describe physical structures from a logical point of view. With this distinction between the logical and physical information, value systems were developed which could integrate all the data of a given application into one collection.

The fourth generation consisted of relational databases and began in the 1980s, resulting in database systems that could store data redundancy free under a central control and in a clear distinction between physical and a logical data model. Systems based on relationship modeling occurred during this period of time. The systems based on relationship modeling are provided with a high degree of physical data independence and the availability of powerful languages. Less of the system is visible to the user, with changes taking place in the background. A shift from record orientation to set orientation marks this fourth generation.

As of 1991, there was a fifth generation predicted, post-relational, which we are currently experiencing, and perhaps surpassing. Other applications can benefit from database technology. The development of extensible systems, logic-oriented systems, and object-oriented systems are part of this generation. R.G. Cattel speaks of the changes seen in the last fifteen years:

"The past decade has seen major changes in the computing industry. There has been a widespread move from centralized computing to networked workstations on every desk. We have seen an entirely new generation of software aimed at exploiting workstation technology, particularly in engineering, scientific and office applications.

In database systems, there have been major changes in products for business applications, including the widespread acceptance of relational DBMSs. However, existing commercial DBMSs, both small-scale and large-scale, have proven inadequate for applications such as computer-aided design, software engineering, and office automation; new research and development in database systems has been necessary. (Cattell 1991)

The very nature of these new object oriented databases has caused changes right down to the programming level. As we near the end of this century, designers are now looking at databases that can predict the side effects of medicines, eliminating the need for human trial subjects. Other programs are being designed to put in data for architecture to check building integrity. Car manufacturers are able to input data and have three-dimensional models to experiment with, regarding stress factors and damage.

With so much new technology erupting every day, some needs have developed for a standardization of protocols and a way to store all the data.

DEVELOPMENTS

Mark Hammond (PC Week) talks about a new development for standardization. IBM has developed DRDA (Distributed Relational Database Architecture) which is a standard interoperability protocol for databases and applications. The DRDA was developed in 1989, and is finally out into the public domain and ready for use.

Data warehousing is a new development on the Information System front, and is actually the culmination of new developments in data technology. Gabrielle Gagnon identifies these developments. They include entity-relationship modeling, heuristic searches, mass data storage, neural networks, multiprocessing, and natural-language interfaces. She goes on to say the data warehouse is a centralized integrated repository of information, one that can provide a vital competitive edge for product development.

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