Data, Data processing, business data processing, data storage, file management system and data base management systems.
Data, Data Processing and Database management System
Data processing and data management are critical components of business organizations.
DATA PROCESSING
Data processing refers to the process of performing specific operations on a set of data or a database. A database is an organized collection of facts and information, such as records on employees, inventory, customers, and potential customers. As these examples suggest, numerous forms of data processing exist and serve diverse applications in the business setting.
Data processing primarily is performed on information systems, a broad concept that encompasses computer systems and related devices. At its core, an information system consists of input, processing, and output. In addition, an information system provides for feedback from output to input. The input mechanism (such as a keyboard, scanner, microphone, or camera) gathers and captures raw data and can be either manual or automated. Processing, which also can be accomplished manually or automatically, involves transforming the data into useful outputs. This can involve making comparisons, taking alternative actions, and storing data for future use. Output typically takes the form of reports and documents that are used by managers. Feedback is utilized to make necessary adjustments to the input and processing stages of the information system.
The processing stage is where management typically exerts the greatest control over data. It also is the point at which management can derive the most value from data, assuming that powerful processing tools are available to obtain the intended results. The most frequent processing procedures available to management are basic activities such as segregating numbers into relevant groups, aggregating them, taking ratios, plotting, and making tables. The goal of these processing activities is to turn a vast collection of facts into meaningful nuggets of information that can then be used for informed decision making, corporate strategy, and other managerial functions.
DATA AND INFORMATION
Data consist of raw facts, such as customer names and addresses. Information is a collection of facts organized in such a way that it has more value beyond the facts themselves. For example, a database of customer names and purchases might provide information on a company’s market demographics, sales trends, and customer loyalty/turnover.
Turning data into information is a process or a set of logically related tasks performed to achieve a defined outcome. This process of defining relationships between various data requires knowledge. Knowledge is the body or rules, guidelines, and procedures used to select, organize, and manipulate data to make it suitable for specific tasks. Consequently, information can be considered data made more useful through the application of knowledge. The collection of data, rules, procedures, and relationships that must be followed are contained in the knowledge base.
CHARACTERISTICS OF VALUABLE INFORMATION.
In order for information to be valuable it must have the following characteristics, as adapted from Ralph M. Stair’s book, Principles of Information Systems:
- Accurate. Accurate information is free from error.
- Complete. Complete information contains all of the important facts.
- Economical. Information should be relatively inexpensive to produce.
- Flexible. Flexible information can be used for a variety of purposes, not just one.
- Reliable. Reliable information is dependable information.
- Relevant. Relevant information is important to the decision-maker.
- Simple. Information should be simple to find and understand.
- Timely. Timely information is readily available when needed.
- Verifiable. Verifiable information can be checked to make sure it is accurate.
DATA MANAGEMENT
Data are organized in a hierarchy that begins with the smallest piece of data used by a computer—for purposes of this discussion, a single character such as a letter or number. Characters form fields such as names, telephone numbers, addresses, and purchases. A collection of fields makes up a record. A collection of records is referred to as a file. Integrated and related files make up a database.
An entity is a class of people, objects, or places for which data are stored or collected. Examples include employees and customers. Consequently, data are stored as entities, such as an employee database and a customer database. An attribute is a characteristic of an entity. For example, the name of a customer is an attribute of a customer. A specific value of an attribute is referred to as a data item. That is, data items are found in fields.
The traditional approach to data management consists of maintaining separate data files for each application. For example, an employee file would be maintained for payroll purposes, while an additional employee file might be maintained for newsletter purposes. One or more data files are created for each application. However, duplicated files results in data redundancy. The problem with data redundancy is the possibility that updates are accomplished in one file but not in another, resulting in a lack of data integrity. Likewise, maintaining separate files is generally inefficient because the work of updating and managing the files is duplicated for each separate file that exists. To overcome potential problems with traditional data management, the database approach was developed.
The database approach is such that multiple business applications access the same database. Consequently, file updates are not required of multiple files. Updates can be accomplished in the common database, thus improving data integrity and eliminating redundancy. The database approach provides the opportunity to share data, as well as information sources. Additional software is required to implement the database approach to data management. A database management system (DBMS) is needed. A DBMS consists of a group of programs that are used in an interface between a database and the user, or between the database and the application program.
DATA ORGANIZATION.
Data organization is critical to optimal data use. Consequently, it is important to organize data in such a manner as to reflect business operations and practices. As such, careful consideration should be given to content, access, logical structure, and physical organization. Content refers to what data are going to be collected. Access refers to the users that data are provided to when appropriate. Logical structure refers to how the data will be arranged. Physical structure refers to where the data will be located.
One tool that database designers use to show the logical relationships among data is a data model, which is a map or diagram of entities and their relationships. Consequently, data modeling requires a thorough understanding of business practices and what kind of data and information is needed.
