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January 1975 with the announcement of the MITS ALTAIR (Figure 513). Built by Micro Instrumentation and Telemetry Systems (MITS) in Albuquerque, New Mexico, the ALTAIR was designed around the Intel 8080 microprocessor and a specially designed 100-pin connector. The machine ran a BASIC operating system developed by Bill Gates and Paul Allen; in effect, MITS was Microsoft s first customer. The ALTAIR was really a hobbyist s machine, but soon the market shifted to a small business focus. Machines like the Apple, Osborne, and Kaypro were smaller and offered integrated keyboards and video displays. In 1981, of course, IBM entered the market with the DOS-based personal PC, and soon the world was a very different place. Apple followed with the Macintosh and the first commercially available graphical user interface (GUI), and the rest, as they say, is history. Soon corporations embraced the PC; a chicken in every pot, a computer on every desk seemed to be the rallying cry for IT departments everywhere. There was a downside to this evolution, of course. The arrival of the PC heralded the arrival of a new era in computing that allowed every individual to have his own applications, her own file structures, and his own data. The good news was that each person now controlled his or her own individual computer resources; the bad news was that each person now controlled his or her own individual computer resources. Suddenly the control was gone: Instead of having a copy of the database, there were now as many copies as there were users. This led to huge problems. Furthermore, PC proliferation led to another challenge: connectivity, or lack of it. Whereas before every user had electronic access to every other user



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for the turning point models; training resulrs for the turning point models) * Trading Results for All Models (@ading results for the reverse slow %k model: frading results for the bottom ruming point model; trading results for the top turning poinf model) * Summary Analyses l Conclusion * What Have We Learned

Figure 5-13 The ALTAIR 8800 computer (Photo courtesy Jim Willing, The Computer Garage)

Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website.

Data quality varies from excellent to awful. Since bad data can wreak havoc with all forms of analysis, lead to misleading results, and waste precious time, only use the best data that can be found when running tests and trading simulations. Some





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Before creating an entity data model, consider Figure 6-22, which shows a diagram of the ApressBooks database having two tables and one association between them:

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via the mainframe or minicomputer-based network that hooked everyone together, the PC did not have that advantage. Furthermore, PCs eliminated the efficiency with which expensive network resources such as printers could be shared. Some of you may remember the days when being the person in the office with The Laser Printer attached to your machine was akin to approaching a state of Nirvana. You were able to do your work and print anytime you wanted except, of course, for the disruption caused by all of those people standing behind you with floppy disks in their hands promising you that It s only one page it ll just take a second. Thus was born the term Sneakernet; in order to print something, you had to put the document on a diskette (probably a 51/4inch floppy, back when floppies really were floppy), walk over to the machine with the directly attached printer, and beg and wheedle for permission to print the file not the most efficient technique for sharing a printer. Something else was needed. That something was the local area network (LAN).

forecasting models, including those based on neural networks, can be exceedingly sensitive to a few errant data points; in such cases, the need for clean, error-free data is extremely important Time spent finding good data, and then giving it a final scrubbing, is time well spent Data errors take many forms, some more innocuous than others In real-time trading, for example, ticks are occasionally received that have extremely deviant, if not obviously impossible, prices The S&P 500 may appear to be trading at 95200 one moment and at 25050 the next! Is this the ultimate market crash No-a few seconds later, another tick will come along, indicating the S&P 500 is again trading at 95200 or thereabouts What happened A bad tick, a noise spike, occurred in the data.

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