Databases Reference
In-Depth Information
but only if that first object is the focal object. If not, then the Market
Basket Analysis would skip the first object and pick up the second object
and consider all the other objects in the context of that second object, but
only if that second object is the focal object. This process continues for
every object in the Itemset, even if the focal object is found somewhere
in the middle of the Itemset. The search for the focal object in the Itemset
continues because the person generating the Itemset may have chosen to
include an object twice. Logically then, Market Basket Analysis juxtaposes
each object, one at a t ime in its own turn, against all the other objects
in the Itemset. This is a recursion of the Itemset, juxtaposing each
n
th
object in the Itemset with all other objects in the Itemset. By the way, an
individual object may occur multiple times, and not in contiguous order,
within a single Itemset. The logic that juxtaposes a Driver Object with all
Correlation Objects must be able to resolve all the multiple occurrences of
each object into a single occurrence of that object.
As mentioned previously, procedural logic in a stored procedure is able
to perform a recursion by considering one Driver Object at a time. In each
pass through the logic, procedural logic can keep a tally of the Correlation
Objects as having occurred in the context of a Driver Object. Once that
recursion is complete, procedural logic can then move on to the
n
th object
until it reaches the end of the Itemset.
The solution design in Chapter 5 i s able to accomplish the recursion
between a Driver Object and all the other objects in an Itemset by first
capturing each recursion as a row of data. Each row of data juxtaposes
a Driver Object with a single Correlation Object. Then, the set logic of
relational SQL is able to use a SUM and GROUP BY statement to count
the number of occurrences of each Correlation Object that occurred in an
Itemset within the context of a Driver Object. The same relational SQL is
also able to sum any metrics or measurements (e.g., quantity, currency,
points) associated with each Correlation Object.
oN your mArk…Get set…Go!
The solution design in Chapter 5 c annot change the laws of data sam-
pling. Unfortunately, the need to maintain the integrity of the data
sample and simultaneously achieve statistical significance cannot be
removed. However, the large data volumes necessary to deliver statistically
