Relational databases typically store about 20 percent of a company's information. Organizations have spent a lot of time and effort using HTML to make this data presentable to a wider audience. But what if all you're really interested in is the data—not its presentation?
Take the example of a common stock-ticker Web page. The page presents stock prices in an HTML table, as Table A shows. Certain pages will even manage your portfolio for you.
But if you want to track this information yourself and act on it immediately, you would have to repeatedly request this page and break apart the HTML to obtain the five pieces of information you need. And what if a Web designer decides that Currency should appear before Price or to now measure Changes in absolute terms?
What you need is a way to separate this page's content from its presentation. Although the original HTML specification does a decent job of this, the browser- and layout-specific tags quickly muddy the original specification. To transform the original data into a format we can use, it must be in a reasonably self-describing format, like the following XML:
***** 25 200 +20
You can quickly convert data in this format into HTML for a Web page or run the data through a rules engine that sends the alert "Sell!" In fact, if you provide the data in this format, other people can do whatever they want to with it.
Although you can separate data from its presentation with comma-delimited files, ADO record sets, or any number of other technologies, XML is platform-independent, has many well-documented standards, and features a large number of tools and utilities to simplify a database and application developer's life.
For e-commerce and business-to-business companies, which are attracting huge influxes of venture capital and seeing stock prices go through the roof, XML is an obvious choice for data transportation because "everybody is doing it." While such peer pressure isn't always the best reason for choosing a technology, the fact that so many organizations are settling on one industry-standard description of data is a powerful incentive to join in. And if everyone uses the same vocabulary, you can streamline your business processes.