Data vs. Information: Differentiation

Database Systems Design, Implementation, and Management, 6e
Chapter 1: Database Systems

ISBN: 061921323X Author: Peter Rob, Carlos M. Coronel
copyright © 2005 Course Technology

1.1 Data vs. Information

To better understand what drives the design of databases, you must understand the difference between data and information. Data are raw facts. The word “raw” is used to indicate that the facts have not yet been processed to reveal their meaning. For example, suppose that ROBCOR Company tracks all sales for its two divisions through invoices. Each of the invoices contains raw facts such as these:

invoice number = 300124 invoice date = 12-JAN-2004 sales amount = $125.98

Further suppose that ROBCOR’s two divisions have generated 1,380,456 and 1,453,907 invoices, respectively, between the first quarter of 1999 and the first quarter of 2004. Therefore, ROBCOR’s raw data include 2,834,363 invoice numbers, 2,834,363 invoice dates, and 2,834,363 sales amounts. Given such an abundant data environment, coupled with employee data for each of the two divisions for each of these quarters, how likely is it that ROBCOR’s managers can draw useful conclusions about sales productivity per employee for each of the two divisions? Examining these 2,834,363 invoices individually will merely overwhelm ROBCOR’s managers. On the other hand, if they process these facts to yield total sales per quarter for each of the two divisions, and then divide these quarterly sales summaries by the quarterly employee count, as shown in Figure 1.1, ROBCOR’s managers will have information, that is, data processed to reveal meaning. These results make it quite plain that the employees of Division 1 have greater sales productivity per employee than those of Division 2. Moreover, it’s easy to see that the sales productivity gap is widening. Such information can then be used as the foundation for decision making. Data processing may be as simple as organizing the data to reveal patterns or as complex as statistical modeling to make forecasts or draw inferences.

Figure 1.1 Sales per Employee for Each of Robcor's Two Divisions

[Click to enlarge]

Our era is called the “information age.” This term recognizes that the 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.

Let’s summarize some key points:

* Data constitute the building blocks of information.
* Information is produced by processing data.
* Information is used to reveal the meaning of data.
* Accurate, relevant, and timely information is the key to good decision making.
* Good decision making is the key to organizational survival in a global environment.

Timely and useful information requires accurate data. Such data must be generated properly, and it must be stored properly in a format that is easy to access and process. And, like any basic resource, the data environment must be managed carefully. Data management is a discipline that focuses on the proper generation, storage, and retrieval of data. Given the crucial role played by data, it should not surprise you that data management is a core activity for any business, government agency, service organization, or charity.

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