Let us begin by discussing data and information before delving into the definition of data processing.

Data Processing

Definition of Data

Data refers to unprocessed and unorganized facts or figures. These are raw materials that have not yet undergone any form of manipulation or analysis.

In other words, data is simply a collection of unprocessed information that has not yet been put into a useful form. It can exist in various forms such as numbers, words, images or sounds.

It is important to note that while data itself may not be particularly useful, it is the foundation upon which information is built. Without data, it would be impossible to generate meaningful insights, make informed decisions or gain knowledge about the world around us.

Thus, data is the starting point for the process of generating knowledge and insight from information, and it is an essential component of modern society, particularly in the realm of technology and computing.

There are various sources from which data can be obtained, including but not limited to the following:

(i) Books

(ii) Documents

(iii) Presentations

(iv) Interviews

(v) Worksheets and other similar sources

(vi) Databases

  • Books, documents and presentations are excellent sources of data, providing a wealth of information on a range of topics. These sources may include research studies, historical records, government reports, and other written works.
  • Interviews are another valuable source of data, providing firsthand accounts and personal insights that can be difficult to obtain through other means. These interviews may be conducted in person, over the phone or online, and can provide important context and perspective on a particular subject.
  • Worksheets, surveys and other forms can also be a useful source of data, providing structured and organized information on a specific topic. These sources can include both quantitative and qualitative data and can be used to gain insights into a wide range of issues.
  •  Databases can be an excellent source of data, providing a wealth of information on a range of topics. These sources may include government databases, academic research databases, and private sector databases, among others. The data in these databases may be structured or unstructured and can include information on everything from demographics and consumer behaviour to financial data and scientific research

Types of Data

Data can be categorised into four different types, namely alphabetic, numeric, alphanumeric and symbolic data. These types of data can be further explained as follows:

  1. Alphabetic Data: This type of data consists solely of letters of the alphabet, such as A, B, X and W.
  2. Numeric Data: Numeric data comprises only numerical figures, for example, 1, 7, 20 and so on.
  3. Alphanumeric Data: Alphanumeric data contains a combination of letters and numbers, such as Y2K.
  4. Symbolic Data: Symbolic data refers to any data that is represented by a symbol, such as +, {},. > and <. information is the processed form of data that has been analysed and given meaning. It is data that has been organised and interpreted in a way that allows it to be used to inform decisions and actions.

Sources of Information

Primary Source

A primary source is the original or first-hand account of information. For instance, an eyewitness to an event, a document that is being investigated, or a person who was present at a particular location. Such sources offer direct access to information that has not been filtered, interpreted, or altered by others.

Secondary Source

the secondary source refers to information that has been already created or interpreted by someone else. Such sources could be the internet, television, newspapers, magazines, textbooks, and other published materials. While secondary sources can provide valuable insights, they are not as reliable as primary sources since they are often subject to interpretation and bias

Examples of information documents include: 

The items listed are various types of documents that can serve as sources of information for different purposes.

  1. Report card: This is a document that provides information about a student’s academic performance in a particular period. It shows the grades or marks achieved in different subjects, as well as the overall performance.
  2. Bank account balance: This document shows the current balance of a bank account, which is useful in managing personal finances, making financial decisions, and business transactions.
  3. Identity card: This is a document that serves as proof of identification for an individual. It contains personal information such as name, photograph, date of birth, and other important details that are useful for security and identification purposes.
  4. PHCN bill: This document provides information about the amount of electricity consumed in a particular period, as well as the charges for the consumption. It is useful for budgeting and managing expenses related to electricity usage.
  5. Staff salary: This document shows the amount of money earned by an employee in a particular period, including deductions and taxes. It is useful for budgeting and managing personal finances.
  6. Advertisement of vacancy: This document provides information about job vacancies available in a particular organization, including the requirements, responsibilities, and benefits. It is useful for job seekers who are looking for job opportunities.
  7. C-caution: This is a document issued to a traffic offender by law enforcement agents, indicating the traffic offence committed and the fine to be paid.
  8. Zebra crossing: This is not a document but rather an indication on the road that informs road users to stop and yield to pedestrians crossing the road
  9. Traffic light showing green, red, and orange: This is also not a document but a road signal that provides information to road users about when to stop, go or slow down. Green means go, red means stop, and orange means to slow down or stop if it is safe to do so

Forms of information

  1. Visual: This type of information is presented in graphical or pictorial form, such as photographs or illustrations.
  2. Oral: Oral information is communicated through speech or spoken words, which could be in person or through media such as radio, podcasts, or phone conversations.
  3. Sensory: This type of information is received through the five senses: sight, hearing, touch, taste, and smell. Examples include the sound of an alarm, the taste of food, or the texture of a surface.
  4. Written: Written information is presented in a hand-written or printed form, such as books, articles, letters, or notes.
  5. Historical: Historical information refers to data or records of past events, transactions, or activities. Examples of such records could include a student’s medical history or educational records.
  6. Electronic: Electronic information refers to data that is transmitted, stored, or accessed via electronic devices and media. Examples include email, text messages, social media posts, or digital documents.
  7. Quantitative: Quantitative information is data that can be measured, expressed, or analyzed numerically. Examples include statistics, financial reports, or scientific measurements.
  8. Qualitative: Qualitative information is data that is descriptive, subjective, and non-numeric. Examples include interviews, surveys, or observations that aim to capture perceptions, attitudes, or experiences

Meaning of Data Processing

Data processing is the process of converting raw data into meaningful information for decision-making purposes. This involves a series of operations, known as data processing steps, which transform the data into usable and comprehensible information.

Data processing encompasses a variety of activities, including digitization, data capture, and data distribution. This can include tasks such as word processing, image processing, and data entry, among others. The goal is to gather information from various sources and convert it into a database that can be easily analyzed and researched.

The process of data processing is crucial for organisations and individuals who need to make informed decisions. Raw data, on its own, can be overwhelming and difficult to comprehend. However, by processing the data, it becomes more meaningful and can provide valuable insights that can inform decision-making.

The various steps involved in data processing include data collection, validation, sorting, transformation, and analysis. Data is collected from various sources and then validated to ensure accuracy and completeness. It is then sorted and transformed into a usable format before being analyzed to draw insights and conclusions.

History of Data Processing

Data Processing is a crucial aspect of the computer industry, just as the Internet is pivotal for databases. Interestingly, Data Processing dates back almost 60 years before the advent of electronic computers.

The history of Data Processing can be traced back to 1890 when Herman Hollerith was commissioned by the US Census Bureau to create a specialized system to analyze census data. This system involved punching holes into data cards to record information, which was then read by mechanical card readers at a census office. Mechanical adding machines were then used to tabulate the results. This process marked the birth of Data Processing, long before the arrival of electronic computers.

In the 20th century, the role of electronic computers in Data Processing became more significant with the invention of ENIAC and UNIVAC. In 1953, IBM introduced its first commercial Data Processing computer, the IBM 701. Subsequently, different computers were designed for business and scientific Data Processing purposes.

One of the early computers designed specifically for Data Processing was the Harvard Mark 1. This computer was used for a variety of tasks such as calculations, cryptography, and statistical analysis.

Data Processing is an essential component of modern-day computing, and it is used in various industries such as finance, healthcare, and manufacturing. The ability to process vast amounts of data quickly and accurately is critical to making informed decisions and gaining a competitive advantage. As technology advances, the role of Data Processing in the computer industry will continue to grow and evolve.

Types Of Data Processing

there are several types of data processing. They include:

  1. Manual Data Processing: This refers to the use of human hands and brains for processing data. For instance, when someone does calculations without the aid of a calculator or computer.
  2. Mechanical Data Processing: This refers to the use of mechanical devices to process data. An example is a teacher using a calculator to compute students’ grades.
  3. Electro-Mechanical Data Processing: This is the use of electronic devices that do not qualify as computers to process data. Such devices require electricity, and examples include cash registers in supermarkets and counting machines used by bank cashiers to count money.
  4. Electronic Data Processing (EDP): This type of data processing mainly involves the use of computers to process data. A teacher who uses Microsoft Excel to process students’ grades or an accounts clerk who uses a computer to process staff payroll is engaging in the data processing. EDP has revolutionized data processing because it allows for faster and more accurate processing of data than any other method. EDP has numerous applications in various fields such as finance, healthcare, and manufacturing. It helps to reduce human error, increase efficiency, and save time.

    Data processing cycle

    1. Data Collection or Gathering: This process, also known as data origination, entails the accumulation of all information or data necessary for a particular purpose. It includes gathering original data and preparing it for entry into an information system. Data can be collected through various methods such as oral interviews, questionnaires, observations, experiments, and scrutinizing reports.
    2. Data Collation or Preparation: Once the data has been collected, the next step is to collate or organize the information in a coherent and systematic manner. This process involves arranging the data, ensuring completeness and accuracy, and recording the facts derived from the collected information.
    3. Data Input Stage: This stage involves inputting the sorted and prepared data into the processor. This task can be carried out by a computer operator using various computer input devices such as keyboards, mice, joysticks, light pens, trackballs, scanners, graphic tablets, microphones, optical character readers (OCR), bar code readers, and optical mark readers (OMR).
    4. Data Processing: In this stage, various calculations such as arithmetic operations (+, x, /) or logical operations (>, <, =) are performed, and new data is generated as a result. Data is also processed in different ways such as classifying or grouping, sorting, summarizing, etc.
    5. Storage Stage: After processing, the information obtained is then stored. It can be stored internally or on different storage media such as magnetic disks (hard disks), floppy disks, external drives, etc.
    6. Output Storage: This stage involves presenting the information obtained from previous stages in a readable and understandable form. Reports are written and kept as output storage, and information can be displayed in various formats such as text, diagrams, sound, video, etc. The aim is to provide or produce information that is useful and relevant for a particular purpose

    Data Processing

    1. Calculation: This refers to the process of carrying out mathematical operations, such as addition, subtraction, multiplication, and division, to obtain a result.
    2. Sorting: This is the process of arranging data in a specific sequence or order, such as in alphabetical or numerical order, to enable easy and quick access to the required information.
    3. Classifying: This process involves grouping data based on shared characteristics, such as age, gender, height, class, etc. The aim is to categorize the data and identify patterns, trends, or relationships that may exist within the data.
    4. Summarizing: This process entails condensing a large amount of data into a brief and concise form, without omitting any vital information. The objective is to present a clear and succinct overview of the data to facilitate decision-making, analysis, or reporting. This can be achieved through techniques such as statistical measures, charts, or graphs, that help to highlight key insights and trends within the data
    5. Validation: This is the process of checking data for accuracy and consistency to ensure it is free from errors or inconsistencies. Validation techniques include verification, where data is compared to a known value, or validation rules, which ensure that the data entered conforms to pre-defined criteria.
    6. Analysis: This process involves examining and interpreting data to identify patterns, trends, and insights that can inform decision-making or problem-solving. Analysis techniques include statistical analysis, data mining, and predictive modelling, which help to uncover hidden relationships or correlations within the data. The results of the the analysis can be presented in various formats such as tables, charts, or reports to help stakeholders make informed decisions.

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