Understanding Hierarchies

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By David Loshin

Defining standards for group classification helps in reducing confusion due to inconsistencies across generated reports and analyses. In the automobile classification example we have been using for the past few posts, we might pick the NHTSA values (mini passenger cars, light passenger cars, compact passenger cars, medium passenger cars, heavy passenger cars, sport utility vehicles, pickup trucks, and vans) as the standard.
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Standardizing Classifications

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By David Loshin

In the most recent post, we posed a straightforward problem: if we have a reporting or analytical objective that depends on using a dimension for classification, what happens when two different value domains are presumed to map to the same conceptual domain?

More concretely, the example we used was mapping individuals to their car
purchase preferences, but different applications used different car
classifications that did not share the same number of values and the value sets
did not directly map in a one-to-one manner.… Read More

The People You Should Care About Most

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By Elliot King

This goal should be a no-brainer. When a customer interacts with your organization, your point-of-contact personnel should have accurate information about your products and services and about the person especially in the case of a repeat customer. When front-line personal provide incorrect or incomplete information, or don’t have access to information they should have, the customer experience suffers.
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Mistakes Are All Around Us

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By Elliot King

Mistakes happen. No matter how effective your data quality program is; no matter how well trained your personnel are; no matter how aware you are of the high cost of low data quality, data errors will creep into your databases. The reason is simple. Before information winds up in a database, it passes through a series of steps involving both human interaction and computation from data acquisition to archival storage.
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Centricity and Connections: Clearing the Air

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By David Loshin

There are opportunities for adjusting your strategy for customer centricity based on understanding the grouping relationships that bind individuals together (either tightly or loosely). And in the last post, we looked at some examples in which linking customer records into groups was straightforward when the values to be compared and weighted for similarity are exact matches. When the values are not exact, it introduces some level of doubt into the decision process for including a record into a group.

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