GIVEN:

A spreadsheet containing a dozen "blocks" of constants data.

Each block consists of 16 columns and 12 rows of constants,
and each block relates to a named, geographical location
(already present in an existing db).

The columns represent selected hours of the day (from 0500
to 2000), in text format (numbers as text).

The rows represent the twelve months of the year in number
format.  The Constants are similar to "11.96", without the
quotation marks.

TASK:

Quickly (what else is new?) make these constants available
for data analysis in an Existing Access database, and set up
a query to average the constants that match a) a certain
"block" of the constants; b) the month of the year; c) given
a Start Time and a Finish Time, whatever constants would be
included where a half-hour or more would be included in the
time span.  Like (assume constants block 1 and first month
of the year):

    Start Time = 0635
    Finis Time = 1125

    Then include hours 0700, 0800, 0900, 1000.

    Then lookup the constants that match the criteria,
    and produce an average (mean) constant for copying
    to another (yuk!) spreadsheet that the boss uses to
    do further analysis.

MY THOUGHTS:

#1

Probably the pro's would say, put all the constants in a
single table, where:

    column 1:  Autonumber Id
    Column 2:  Foreign key to relate to Block
    Column 3:  Month of year
    Column 4:  Hour of the day
    Column 5:  Constant

The first question with this approach is how to get the data
morphed into that configuration?  At my skill-level, all I
can think of is manually horsing the data around (blah!  And
I'd probably ruin it, in the process).

#2

An alternative method would be to leave the structure of the
blocks as they are, and simply string them all into a single
table.

This would be much quicker to set up, but I'm not sure about
ease of use later on.

#3

Yet another alternative would be to make a separate table
for each block.  That would probably be the easiest way to
table the data, but I doubt that would be easy to live with
after making the tables.

YOUR THOUGHTS HERE:

(pretty-please...)