Data Warehousing and Web Engineering

Citation

Mason, D. (2003), "Data Warehousing and Web Engineering", The Electronic Library, Vol. 21 No. 6, pp. 615-615. https://doi.org/10.1108/02640470310509216

The boom and bust of the dot.com revolution had many lasting effects, not least of which was the emergence of a new discipline called Web engineering. The earliest commercial Internet sites were simple displays of product information, all surface glitz with no depth. E‐commerce competition rapidly resulted in the triumph of content over presentation. However, simply removing flashy graphics did not make an e‐commerce site. Customers wanted usability, and companies soon found that security and reliability had to be built‐in or customers would go elsewhere. Incorporating these into an e‐commerce site, integrating online transactions with routine systems and enforcing standards are what Web engineering is about.

However, Web engineering is about more than effective e‐commerce. Its overall aim is to integrate all of an organisation's data, past and current, and make it available to whoever needs to use it, online or internal. Data warehousing is the collective name for the methods that Web engineers use to find, integrate, analyse, and display this legacy data, uncovering the information locked deep in the archives.

The science of data warehousing consists of architectures for organising data so that it can be accessed easily no matter how old or complex the records are, and data mining techniques, mathematical and artificial intelligence procedures used to interrogate and present the data.

This book contains 18 articles on aspects of data warehousing and data mining. All of the articles have been published elsewhere in Idea Group publications. Six have appeared in the Journal of Database Management, and one in the Journal of End User Computing. All the others have appeared already in other edited collections of articles. In fact, seven of them come from one book, Managing IT in a Global Economy, replicating about a third of it.

The reason for the selection of these particular articles is not clear, and is not addressed by the editor. The treatment of the subject is very variable. The first article is an over‐enthusiastic beginner's guide to IT and business intelligence, probably written before the dot.bomb meltdown, and pitched at the level of explaining how bar charts can be used to display data. On the other hand, many articles give full mathematical treatments of complex algorithms. The very next article, for example, is a 54‐page exploration of n‐dimensional table schemata. Just for contrast, article four manages to race from introduction to conclusion in less than two pages, ostensibly showing how to apply financial market call options to data warehousing spending.

The republished journal articles are similarly mixed. One explores the implications of the metaphor used in data warehousing, a sociological view of the issues, most of the others are standard computer science mathematical treatments of architectures, algorithms and applications. Some are tests of experimental algorithms and data structures, others are conceptual models and theoretical treatments of search styles. Certainly there is a wide range of approaches, from university labs around the world.

From this disparate collection it is difficult to tell who the book is aimed at, since the editor omits to mention it. Overall, the selection of articles presented has no obvious appeal to either researcher, student or business user and it is difficult to see where its market lies.