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Having left and lost the troops early on, I've retreated back to
base camp. There I hope to recapture the momentum apparently I
never had in the first place. I had hoped to get into some detail
in data capture of data design, i.e. what context in which to
place the content. Notice I don't say database design or file
design because the rules for data design are not dependent upon
any particular data management method used. Restated data design
is independent of data management.
This arises because all data is stored serially, bitwise in every
storage medium. This says the optimum data design is the same
regardless. The optimum data design is determined strictly by
data usage, an aggregate of its frequency of use (access) and the
volume per use (instances retrieved). These deal with
presentation of the data. The presentation is the output
structure (context). Thus the optimum data design is determined
strictly by the context(s) used.
Now understanding the difference between data and information
(data plus meaning), means that for a given set of data the same
information, i.e. the meaning gained by the observer, exists
regardless of context. The only possible difference among
contexts is the rate at which the information, i.e. the meaning,
is acquired. The optimum context is one whose rate of acquisition
is not less than any other.
Now the highest rate implies the greatest meaning in the least
time. If you are an enterprise engaged in transaction processing
in very high volumes, the rate, the presentation structure (the
data context), becomes very important. Coupled with the
absorption rate of the observer is the processing rate, i.e. the
amount of work, required to transform the stored data into the
presentation data. Here again you want to get the most out with
the least effort.
"Fine", you say, "but what does it have to do with using MESA 2
for investments?" Well, it's your time and it depends upon what
value you place upon it. Not simply in monetary terms, though
certainly they exist, but in terms of quality time, time available
for other purposes. So why not engage in an optimal (stored) data
design based upon an optimal set of (output) presentation designs?
As Peter then starts us on our journey on investments and the data
and the processing that we need to do, then lets do so with a
sense of preparing our data, its input, maintenance, and output
that minimizes our ongoing effort.
As part of this we can discuss the challenges that Peter has
raised relative to his use of stored data streams. It's possible
that his method is optimal. If so, we have provided a metric for
its determination.
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2001 ]
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