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At some point in your life you ve had to ll out a form with details like your name, your date of birth, your address, and so on phone number, e-mail, citizenship the list is endless. Whether it was a paper form or something you lled out online, your answers had to t. (Even if you could attach additional pages as needed, your answers had to t in the envelope or mailbox!) Furthermore, if the information you provided was destined for a well-designed database, the information had to t not only the form but also (after interpretation by a data entry clerk, a software interface, or another intermediary) the constraints of the database design. For this example, suppose that the forms we re thinking about are receipts from individual sales and that these forms have a place for, among other things, the date of the sale and the tax paid on the sale. Down the road, these forms are entered into a database, and the data may be used to generate a report perhaps a report of tax receipts by month. To produce the report, the sales data has to be partitioned, or grouped, into months, according to the sale date, and the tax receipts have to be added up for each month. However the data is represented, we have to be able to gure out a month and a number from each receipt. Because you re reading this book, it s probably safe to assume that you ve had to think about this kind of process. You ve probably had to get your hands dirty in it. More likely than not, you ve also had the experience of seeing or worrying about information that looks like the information in Table 2-4.
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TABLE 2-4
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Sale Dates and Tax Received for Some Sales
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Jul 3 Sunday, 10/3 Sunday, 10/3 10/12/2007 10-13-2007
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Tax Collected
$1.24 exempt Carole Poland N/A $3.00 $1.24
Customer Name
Mark Hassall Torstonen $2.56 CAROLE POLAND POLAND Yao-Chiang Did not provide
11 11 12 I3 14 #17 18
10-13-2007 Febuary 07 February 11 Feb 13 2/13/07 14 Feb Carole Poland
$18.24 3.10 .41 2.25 5
katrin FRNDO Jim Wickam (sp ) Sittichai blank
Not even the most talented programmer can write procedures to report tax receipts by month from data like this well, not procedures that produce correct reports. The requirement is incompatible with the data, and one or the other has to be bent.
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Let s assume the data is bent into shape, and instead of the unmanageable information in Table 2-4, the data appears as shown in Table 2-5.
TABLE 2-5
Sale Dates and Tax Received for Some Sales
Sale Date
7/3/2007 10/3/2007 10/3/2007 10/12/2007 10/13/2007 10/13/2007 2/25/2007 2/15/2007 2/29/2007 3/13/2007 3/16/2007 3/12/2007 18.24 3.10 0.41 2.25 5
Receipt Number
1 2 3 6 7 11 11 12 13 14 17 18
Tax Collected
1.24 exempt 2.56 0 3.00 1.24
Customer Name
Mark Hassall Torsten Arndt Yao-Qiang Cheng Carole Poland Carole Poland Yao-Qiang Cheng NULL Katrin Gulbis Nkenge McLin Jim Wickham Sittichai Tuntisangaroon blank
If you looked closely, you may have noticed something strange about receipt 13 s sale date. In the row containing 13 in the Receipt Number column, the Sale Date column contains 2/29/2007, which doesn t represent a date. The Sale Date column still contains strings, not dates. While most of the values this time do represent dates, not all of them do. Whether we use strings, numbers, or another data type, we need a column that holds faithful, unambiguous representations of dates. Note Wish as we might, someone, if not us, has to accommodate the receipt that has an
illegible or missing date. Recognizing the value of a column to hold faithful, unambiguous representations of dates when they existed, which might not be always those responsible for SQL provided for nullable column declarations. I won t have too much to say about NULL, I m afraid. The mathematics becomes much harder some might say intractable if you attempt to accommodate NULLs.
Dates and literal date strings aren t the same, literal date strings and strings aren t the same, and the interpretation of literal date strings isn t invariant from culture to culture, epoch to epoch, or system to system. The best we can do is document and de ne categories (such as dates), identify one or more faithful representations of them (such as date strings in a particular format), and understand and record as much as we can about the representations and concepts, their cultural interpretations, and what universe of potential values serves as the domain of discourse for a category. The data in Tables 2-4 and 2-5 contain other properties that will make it hard to create a tax report. I won t say anything about them, but I encourage you to think about why, mathematically, they cause problems.
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