Electronic Data Interchange (EDI)
Historically, when a business started to automate functions like orders and invoicing, the systems it developed were only useful to that organisation. For example, a company might generate an order and send it to a second company. That second company couldn't just take the order and process it electronically!! It had to take the order, re-enter the details of the order in to its own system and then action it! This was because each of the two companies had its own systems for doing things. Clearly this is a waste of resources. EDI was developed to provide an between two separate computer systems. Each company could have its own way of doing things, but by using EDI, they could now 'talk' to each other without one company having to re-enter data or redesign its system to match the other company's.

(VANs)
As EDI became more widespread, enhanced communication links between companies were offered by companies. These simplified the communication links between companies but also provided extra services that improved the way information was passed between them. They provided, for example, services that:

o Allowed different EDI to be used by different companies.
o Allowed companies to data within the VANS so they could more easily be accessed from outside the company, for example, by other organisations.
o Allowed audit trails so that the history and progress of the information being exchanged could be recorded and traced if necessary.
o Provided a vehicle by which companies could set up an EDI trading agreement.
o Provided the technical know-how for companies.

Data warehousing
Data warehousing has been around since the 1990s. The idea behind data warehousing is that

o data, mainly from past transactions and orders that the company has carried out, are separated out from the business.
o The data is re-organised in such a way as to allow it to be analysed.
o The newly structured data is then queried.
o The results of the query are reported.

Data warehousing could be used as a predictive tool, to indicate what should be done in the future. However, the main use of data warehousing is not as a predictive tool but as a tool, to monitor the effects of previous operational decisions made in the course of a business. For example, if Marks and Spencers decided to open stores in Asia, data could be collected as the stores opened and over the first few months. This could then be passed to a data warehouse. The wisdom of opening stores in Asia for the business as a whole could then be reviewed and conclusions backed up with statistical evidence.

Data mining
Data mining burst onto to the scene only a few years ago. Data mining is the term applied to the software technique that looks at a huge set of data and tries to find hidden in it. Data mining can be used to answer such questions as "Who is most likely to buy a book at Christmas?" and "Why are they more likely to buy a book at Christmas?" The most important thing to remember about the role of data mining is that it is . It seeks to answer questions about the future. Compare this to the retrospective use of data warehousing.

Data mining (and data warehousing) has become possible in the last few years for a number of reasons:

o Sophisticated software is now available.
o Vast data is possible.
o Vast processing power is available, for example using processors.
o The price of sophisticated hardware has fallen dramatically
o It is far easier to collect and process information because so much of a company's business is now .