Data Processing – The Cycle, Systems and 5 Useful Types of Processing

Understand the concept of data processing and use cases. Delve into the processing cycles and their components. Briefly check out eight kinds of data processing operations. Also learn about electronic data processing systems, their advantages and five types of processing.

Definitions of data processing

Data processing is the manipulation of data into a more useful form. Includes; numerical calculation, operations(e.g. classification of data), transmission of data from one place to another. Organizations undertake data processing activities to obtain information with which to control and support the following:

1. Production/operations e.g. manufacturing resource planning, manufacturing execution systems, process control.
2. Marketing activities e.g. customer relationship management, interactive marketing, sales force automation etc.
3. Human Resource Management e.g. compensation analysis, employee skills inventory, personnel requirements forecasting.
4. Financial activities e.g. cash management, credit management, investment management, capital budgeting.
5. Accounting activities: order processing, inventory control, accounts receivable, accounts payable, payroll, general ledger

The processing cycle

There are two types of processing cycles, the Basic Data Processing cycle and the Expanded Data Processing cycle. Basic Data Processing cycle – Consists three basic steps, input, processing and output.

Input: Initial data or input data are prepared in some convenient form for processing. E.g. computers input data is recorded into input medium such as internal memory, cards, disks, flash etc.

Processing: Input data are changed, usually combined with other information to produce data in a more useful form. E.g. pay checks may be calculated from the time cards or a summary of sales for the month may be calculated from the sales orders.

Output: Results of the preceding processing step are collected. The output data/result form depends on the use of the data. E.g. pay checks for employee, printed summary of monthly sales for management, or data to be stored for further processing.

Expanded Data Processing Cycle – More steps; Origination, Distribution, and Storage. Origination: refers to the processes of collecting the original data into source documents. E.g. graded test papers.

Distribution: refers to distribution of the output. Recordings of the output data are often called report documents. E.g. class grade sheets.

Storage: crucial step in many data processing procedures. The processed results are stored for use as input data in the future. A unified set of data storage is called a file which consists of records. A collection of files forms a database. Explore further topics on data processing here.

Data processing operations

Recording: is the transferring of data onto some form or document. The operation occurs during origination, and distribution steps, and throughout the processing cycle.
Duplicating: refers to reproducing the data onto many forms or documents.

Verifying: since recording is usually done manually, it is important that the recorded data be carefully checked for errors. E.g. typed reports are reread for correctness.
Classifying: refers to separating of data into categories.
Sorting: is arranging data in a specific order.

Merging: this operation takes two or more sets of data, all sets having been sorted by same key, and puts them together to form a single sorted set of data.
Calculating: refers to performing numerical calculations on the (numerical) data.
Summarising and report writing

Types of Data Processing (DP) systems – Devices so far have evolved into three types

1. Manual mechanical devices; for calculation & processing data, dark ages (5000 B.C – 1890 A.D). Simple, motorized by human hand e.g. Abacus (5000 B.C.), Oughtred’s Slide Rule (1632), Pascal’s Calculator (1642) etc.

2. Electromechanical devices: powered by electric motor, switches and relays for control of processes e.g. desk calculators and punched card processing devices. The electromechanical devices; middle ages (1890 – 1944).

3. Electronic devices: modern age begun in 1944 – date. It includes the modern computer which have evolved into five generations with advancement of processing hardware; the vacuum tubes, transistors, integrated circuits and microprocessors.

Advantages of electronic data processing

Speed and Accuracy

Automatic operations

  • Most important advantage of modern Electronic computer
  • Cary out a sequence of many different data processing operations without human intervention
  • Automation is possible through stored program

Decision making capability

  • Computer can perform certain decision instructions automatically
  • Determining whether a statement is true or false
  • Based on that results, choosing one or the other course of action out of alternatives

Types of Electronic Data Processing (EDP) systems

Classification of EDP systems according to the way data is processed; example:

  • Response time, time elapse between data input/inquiry-result (online, offline & online real-time systems)
  • Number of users & Programs e.g. time sharing programs
  • Degree of Integration of subsystem e.g. DSS

Offline Data Processing System – input data or transactions grouped into batches, and then sorted sequentially before being subjected to computer processing.

Online Data Processing System – Characterized by remote Central processing unit (CPU), two way communication between the CPU and the input or terminal devices and fast data processing responses. Data is input as soon as it is available with files being update most of the time; usually expensive to operate and with processing speeds faster than offline systems.

Online Real – Time Data Processing System – Insignificant time delay between creation of data and the actual processing. The time delay is insignificant when the processed data/information is generated at the appropriate time for managers to make timely decisions. Components include computer, software, terminals, communication network and database.

Time – Sharing Data Processing System – Three basic characteristics; multi-programming, online interaction & real-time response.

Decision-Support System (DDS) – Provides interactive information support to managers and professionals during the decision-making process.

Distributed Data Processing (DPP) System – characterized by mini- or microcomputers (the satellites) for small scale localized based solution. Remote CPU or larger computer for organisational processing or any larger applications for satellite computers. Examples include the hospital Distributed Data Processing.

TYPES OF PROCESSING

Batch processing – Refers to processing of data or information by grouping it into groups or batches. The batches handled in sequence of separate stages of processing e.g. validation, sorting, computing etc., at pre-defined frequencies. E.g. a weekly factory payroll is naturally processed weekly.

Online processing – consist of terminals connected to a computer and communication by lines that connect different department of the business/system to a computer.

Interactive processing – examples include online order processing, online building society transactions, online payroll processing and online point of sale (supermarket) check out systems.

Real-time processing – examples include airline seat reservation system, online warehouse stock control, online hotel accommodation system and online banking.

Random processing – examples include online credit inquiries, online product availability inquiries, online account inquiries and online package holiday availability inquiries.

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Amar Al Habsy

Entrepreneur, blogger and digital marketer who enjoys writing awesome and original content on a variety of topics based on experience. Connect: Twitter.

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