The phrases “Data Model” and “Schema” are often used interchangeably as they both represent an architectural model of process flow and standard operating procedure from the perspective of data, information and business intelligence.

The concept of a “model” is that it represents some other construct. Often, models are miniature versions of the full-scale artifact they are built to represent or mimic. When considering the concept of a Data Model (or Schema), it is appropriate to think of this as a scaled down version of “how things get done” defined in terms of the data, information and business intelligence that is required in the process. And while it is correct that “getting things done” requires more than just understanding (materials, money, time, etc.) it is the understanding (or knowledge) itself that enables us to effectively use all of the other resources used required by the process.

It is here that we establish the core definition of a database as “Information about Information” (sometimes referred to as metadata). What we mean by “Information about Information” is as follows:

  • A process or standard operating procedure consists of the correct application of appropriate quantities of resources; time, materials and tools
  • A process also requires an understanding of how to engage the aforementioned resources in the proper sequence and manner
  • A database is a technological asset that allows users to capture, enhance, store and reference information about the resources (source, quantity, cost, price, color, usage instructions, etc.)

Given this definition of the database, the Data Model or Schema that is the core foundation of that database is a definition of how the content that is to be captured, enhanced, stored and referenced is manipulated by both the human resources that are the end users and the technological resources that are the database itself and the computer(s) on which it is operating.

Revision: 2
Last modified: 11 November 2019

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