Fundamentals of Data Processing and Information Systems

Understanding Data and Information

A figure is a symbolic representation (numerical, alphabetical, algorithmic, etc.) and an attribute or characteristic of an entity.

Difference Between Data and Information

Data differs from information; various methods are used to compress information to allow for more efficient transmission or storage.

The amount of information in a message can be understood as the number of possible symbols representing the message. Symbols representing the message are considered meaningful data.

The Data Processing Cycle

Data Processing involves careful and systematic procedures performed to develop, codify, and organize data for analysis.

Four Key Data Processing Steps

1. Data Capture: This involves making an observation in order to "capture" a specific piece of information needed to process and display the appropriate results.
2. Store Data: Saving data on a PC, in a spreadsheet, or other media to prevent loss and to enable future comparisons.
3. Transforming Data: The act of sorting, splitting, extracting, analyzing, and comparing data with other information.
4. Display Data: Presenting the processed information for use.

Evolution of Computing Architectures

Centralized Processing

In the mid-1950s, computers were machines the size of an entire room with the following characteristics:

• A Central Processing Unit (CPU)
• Small amount of RAM
• Secondary storage devices (magnetic tapes)
• Output devices (punch cards)
• Input devices (punch card readers)

Distributed Processing

The history of computing evolved toward distributed processing. Minicomputers, which remained powerful machines despite their name, began to take part in the processes previously reserved for mainframes.

Data Structures and Variables

Arrangements

These are groups of homogeneous data (i.e., data of the same basic type). They are stored contiguously in memory and are referenced by a common name and a relative position.

Qualitative vs. Quantitative Data

• Qualitative: When the observation of a variable is based on a quality rather than a number, such as sex, marital status, or place of birth.
• Quantitative: When the observation of a variable can be expressed in numerical terms, such as age, weight, height, or number of children.