The Subtle Tyranny Of Spreadsheets
pipingguy writes "I found this link on a CAD-related mailing list which questioned the current state of spreadsheet usage. Since using spreadsheets is often only one step away from PowerPoint mastery, I thought it worthy of submission." An excerpt:
"The second distortion caused by conventional spreadsheets is more subtle. It's described in a 1980s paper, written by university researcher Jeffrey Kottemann and others concerning what they called 'Performance, Beliefs, and the Illusion of Control.' The paper described an experiment in which subjects were asked to perform a planning task using different tools, some of them with elaborate what-if capability and others without it." Yup, it's a ZD/Yahoo link, but it raises good questions."
I particularly enjoyed it, and it made me wonder why I've always hated Excel. maybe it's time to forgive...
(I always used to like Pipdream on the Archimedes though. That was a combined spreadsheet and word processor).
Since using spreadsheets is often only one step away from PowerPoint mastery.
.. for "Powerpoint Mastery" have a look at Tufte
"The Cognitive Style of PowerPoint".
Erm
Yes, I know it was discussed here before (as I guess), but still - it is worth a mention.
CC.
TaijiQuan (Huang, 5 loosenings)
One of the biggest reasons is the sort function combined with [l]user error.
If a spreadsheet has more columns that fit on the screen, and is used by more than one person, at some point you can almost count on someone highlighting some, not all, of the columns and then sorting the highlighted columns, and saving the file. When that happens, the highlighted columns are sorted, the rest are left as is. Worst, the next person to use the file doesn't always realize the corruption has occurred.
This was a problem in Office 97 and earlier. I think it was a problem in Office 2k, but I don't remember. I have not tested this on Office XP or 2003.
. 62,400 repetitions make one truth -- Brave New World, Aldous Huxley
You shouldn't be forced to use SQL for manipulating data, you should be restrained from using Excel. ;) The reality of the differences between a spreadsheet and a database is that a spreadsheet lacks the data constraints (relationships) necessary to keep a user from entering bad data. A database can control this (data integrity) to a large degree (depending on your datamodel design).
An example I fight with daily is product attributes. I maintain a n ecommerce database with about 180,000 products, each of which would have, say, a color. The problem is that if I import data from a spreadsheet it might randomly insert spaces in the data (i.e. "Black " or " Black" instead of "Black"), whereas if I get the data entered through our tools, the user selects from a list of colors, and only if the choice doesn't exist do they add a new one.
You mention how people are doing a knee-jerk that 'DB's are sacred'. Yes, they are. So are spreadsheets, the problem is that people bastard-ize their use and end up confused about why they both exist, and how to use them.
Database = Data storage, data consistency, ease of data maintenance
Spreadsheet = Data analysis, data redundancy, lack of data integrity.
That's how I see it, anyhow.
"If voting could really change things, it would be illegal. " - Revolution Books, NY
I use Excel constantly to do layouts for invoices, estimates, cards, presentation, etc. because of the precise sizing control. It looks professional, not cheesy at all, some of the stuff looks like it came from a printer.
As for the database aspect, Excel is well suited for a database table layout, that's one of it's principal uses. Not a relational database, but just simple tables, it great at. There's no reason you couldn't have an address book with hundreds of entries and a dialog box front end made with macros. I did this in the past, worked great.
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The things listed as mean and standard deviation in Excel are sample means and sample standard deviations. If you have a list of numbers, and you assume that they were drawn from some distribution with finite expectation and variance, you can calculate the sample mean (simple average), which is an estimate of the expectation. Then you substract this mean from all your numbers and take their squares. The average of that is an estimate of the variance of the distribution, take the square root for the standard deviation. The nice thing is that these estimates converge to the expectation and variance regardless of distribution. If you do make the additional assumption of Gaussianity, you can also say something about the rate of convergence and the distribution of the estimate. But the basic formulas in Excel and such for sample mean and variance work for any distribution that has a mean and variance.