DATABASE SYSTEMS
To understand what drives database design, you must understand the difference between data and information. Data are raw numbers or other findings which, by themselves, are of limited value to decision makers. Information, on the other hand, is the result of organizing, processing, and interpreting data, thus transforming the findings into facts that are useful to decision makers. For example, the number of new users your clinic serves in a month means little until you compare it with the number of new users from previous months and years to see whether there has been an increase or decrease in the trend over time.
Data are transformed into information by:
Selection: Choosing the data that are useful and adequate for answering the questions that have been posed, and ignoring the data that are useless or inadequate for that purpose.
Interpretation: Analyzing the data to put them into context, uncover patterns or problem areas, and reflect on the meaning of these patterns in relation to the questions being asked.
The overall objective of converting data to information is to describe, explain, predict, and/or evaluate a program and its results.
In this “information age” production of accurate, relevant and timely information is the key to good decision making. In turn, good decision making is the key to business survival in a global market. We are now said to be entering to “knowledge age”. Data are the foundation of information which is bedrock of knowledge that is, the body of information and facts about a specific subject. Knowledge implies familiarity, awareness and understanding of information as it applies to an environment. A key characteristic of knowledge is that “new’ knowledge can be derived from “old” knowledge.
Timely and useful information requires accurate data. Such data must be generated properly, and it must be stored in a