Classification of Corporate Data Part 1 of a 4-Part Series
by Bill Inmon
Originally published April 3, 2014
Most of us are so ensconced in corporate data that we do not spend much, if any, time thinking about the world of corporate data. That is sort of like living in Aspen, Colorado, and never noticing the mountains. Taking time to reflect on the larger picture can yield some real benefits.
Three Major Classifications of Corporate DataThese are three major classifications of corporate data – structured corporate data, unstructured repetitive corporate data and unstructured nonrepetitive corporate data.
In order to understand these three classifications of data, let’s look at some examples.
Every time a sale is made or a sales contact or a bank withdrawal is made, a transaction is generated. Typically the transaction ends up as a structured record. There are literally thousands of examples of structured data. Bank transactions, sales, inventory management and manufacturing production – each of these events and more result in structured records.
Unstructured repetitive records form perhaps the largest bulk of data in the corporation. When an organization does analog processing, the activities being measured by analog processing become unstructured repetitive records. There are plenty of other kinds of unstructured repetitive records. Records of telephone calls or records of the transmission of an email are examples of unstructured repetitive data. The term repetitive comes from the fact that the data is highly repetitive, both in terms of content and in terms of structure.
The third classification of corporate data is unstructured nonrepetitive data. There are many examples of unstructured nonrepetitive data. There are emails, healthcare records, warranty claims, corporate contracts, call center interchanges, marketing responses and many more types of this data. With unstructured nonrepetitive data, there are many unstructured records but any one record is probably quite different from any other record when it comes to content and structure.
Gaining Value from Corporate DataThese then are some of the ways that corporate data can be classified. So why does this classification make a difference? It makes a BIG difference when it comes to using the data to get value out of it. Stated differently, in order to get value out of corporate data, there are entirely different approaches to achieving value, depending ENTIRELY on the data that is being analyzed.
SOURCE: Classification of Corporate Data
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