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Re: Article about supposed "murky" future for Oracle

From: Mark C. Stock <mcstockX_at_Xenquery>
Date: Sun, 4 Apr 2004 16:32:33 -0400
Message-ID: <>

"Niall Litchfield" <> wrote in message news:40705b73$0$247$

| >
| > how many users know how complex the underlying query is -- and why
| > they care? they DO know their data (or else they are in more trouble
| a
| > database can solve for them) and they have a right, and we have an
| > duty, to present it to them honestly. it is OUR job to ensure that the
| > output from our systems is 'actually correct'
| Often as not people *don't* know the data. Ask questions like "how many
| people does the business employ? How many of those are managers?" In any
| reasonably sized business the chances are even the HR director won't be
| to tell you without one or more reports, and they will not guarantee the
| exactness of the reports, becuase of data entry error etc. In your
| ask the project manager for an estimate of what the spend or hours worked
| date has been, then compare to the recorded figures.

granted, that is too often the case (did i get a bit hyperbolic to make a point?)

by contrast, however, i've had quite a few experiences with end-users saying things like "that just doesn't look right" and "i know that's not true". how much of that would be affected by the types of transaction-agnostic inconsistencies this thread has been discussing is up for debate, but the most likely scenario were inconsistent database reads affect data integrity is in cases where reports must be consistent within themselves, or the exact time of the report is of significance, or other transactions are spawned based on the dirty reads (ie, not all database reporting is for human consumption)

and yes there are data entry errors, which is why we design systems to validate the reasonableness of data as well as audit data changes, and otherwise reduce the potential for human error

and you're right, users will not be as intimately familiar with data they 'own' but that are not the central focus of their job responsibility (your pm hours example) -- but many have aspects of the data that they understand far better than anyone else in the organization

perhaps your figures on inaccurate and not well-understood corporate data reflect an industry tradition of 'good enough - ship it'? -- of course, present company excluded ;-)
perhaps that industry tradition contributes to the acceptance of technologies and techniques that find fuzzy data acceptable, without admitting that the results are actually not actual (or would that be not actually actual?)

;-{ mcs Received on Sun Apr 04 2004 - 15:32:33 CDT

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