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Celebrating 25 Years

Data management’s misconceptions

By Joab Jackson, GCN Staff

On his way to an academic career, Fabian Pascal took a detour into database management systems.

The technology firebrand and database consultant was working toward a degree in social sciences at the University of Haifa in northern Israel. He disliked the available data management tools so much that he started trying to improve them.

After getting a bachelor’s degree in economics, he received a master’s in business administration with a concentration in information technology from Northwestern University of Chicago.

Pascal operates a Web site called Database Debunkings, holds seminars and writes about database management fundamentals. Author of three books on databases, he frequently contributes to trade magazines and Web sites, where his work sparks spirited debate.

Pascal is extremely critical of Extensible Markup Language in database administration and data exchange. A self-described contrarian, he also has bad things to say about Structured Query Language and commercial implementations of the relational database model.

He has consulted for the Census Bureau, the CIA and the IRS, as well as for leading software vendors.

GCN associate editor Joab Jackson interviewed Pascal by e-mail.

GCN: Why do you say Extensible Markup Language is being misused?

PASCAL: XML claims to be an intersystem data exchange technology, but what it was intended to solve is HTML’s lack of semantics. HTML tags express how data is presented or formatted, not what it means. XML tags purportedly express meaning.

If my system sends data to your system, we must agree upfront on what data will be sent (in other words, the meaning) and some physical format. Once we agree on what to send, there’s no need to include the meaning each time data is sent, because the exchange is between systems. Human readability is not an issue.

XML tags are being repeated unnecessarily in every transmitted record when simple delimiters would do. Often XML tags actually overwhelm the data in frequency and size.



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