Data Processing Concepts Data Processing Cycle.pptx
- 2. Definitions of Common Terms • Data refers to the raw facts that do not have much meaning to the user and may include numbers, letters, symbols, sound or images. • Information refers to the meaningful output obtained after processing the data. • Data processing therefore refers to the process of transforming raw data into meaningful output i.e. information. • Data processing can be done: 1. Manually using pen and paper. 2. Mechanically using simple devices like typewriters. 3. Electronically using modern data processing tools such as computers.
- 3. What is Data Processing? Data processing is the collection and manipulation of digital data to produce meaningful information.
- 4. Data Processing Cycle The sequence of activities involved in data transformation from its raw form to information. It is often referred to as cycle because the output obtained can be stored after processing and may be used in future as input. The four main stages of the data processing cycle are: 1. Data collection 2. Data input 3. Data processing 4. Data output
- 6. #1-What is Data Collection? Referred to as data gathering or fact finding ,it involves looking for crucial facts needed for processing. Methods of data collection • Interviews; Questionnaires, Observation, using sampling techniques • Sampling is a technique that involves taking a small number of participants from a much bigger group (population).
- 7. Stages of Data Collection The process of data collection may involve a number of stages. These include: • Data creation: this is the process of identification and putting together facts in an organized format. This may be in the form of manually prepared document or captured from the source using a data capture device such as a barcode reader and be inputted easily in a computer. • Data preparation: the process of preparing raw data so that it is suitable for further processing and analysis. Key steps include collecting, cleaning, and labeling raw data into a form suitable for machine learning (ML) algorithms and then exploring and visualizing the data. Data collected using devices that directly capture data in digital form do not require transcription. • Data transmission: this will depend on whether data need to be transmitted via communication media to the central office.
- 8. #2-What is Data Input? The process where the collected data is converted from human readable from to machine readable form (binary form). The conversion takes place in the input device. Input may also involve: • Media conversion: data may need to be transmitted from one medium to another e.g. from a flash drive to a computer’s hard disk for faster input. • Input validation: data entered into the computer is subjected to validity checks by a computer program before being processed to reduce errors as the input. • Sorting: in case the data needs to be arranged in a predefined order, it is first sorted before processing.
- 9. #3-What is Processing? • This is the transformation of the input data by the CPU to a more meaningful output (information).Some of the operations performed on the data include calculations, comparing values and sorting. #4-What is Output? • The final activity in the data processing cycle is producing the desired output also referred to as information. This information can be distributed and is played to the target group or stored for future use. • Distribution is making information available to those who need it and is sometimes called information dissemination. This process of dissemination may involve electronic presentation over the radio or television, distribution of hard copies, broadcasting messages over the internet or mobile phones etc.
- 10. Errors In Data Processing #1 - Computational errors: Occurs when an arithmetic operation does not produce the expected results. The most common computation errors include overflow, truncation and rounding • Overflow errors: Occurs if the result from a calculation is too large to be stored in the allocated memory space. For example if a byte is represented using 8 bits, an overflow will occur if the result of a calculation gives a 9-bit number. • Truncation errors: Result from having real numbers that have a long fractional part which cannot fit in the allocated memory space. The computer would truncate or cut off the extra characters from the fractional part. For example, a number like 0.784969 can be truncated to four digits to become 0.784
- 11. #2 - Transcription errors: Occurs during data entry. Such errors include misreading and transposition errors 1. Misreading errors: Are brought about by the incorrect reading of the source by the user and hence entering wrong values. For example a user may misread a handwritten figure such as 589 and type S89 instead i.e. confusing 5 for S. 2. Transposition errors: Results form incorrect arrangement of characters i.e. putting characters in the wrong order. For example the user might enter 396 instead of 369. These errors may be avoided by using modern capture devices such as bar code readers, digital cameras etc. which enter data with the minimum user intervention. 3. Rounding errors: Results from raising or lowering a digit in a real number to the required rounded number. for example, to round off 30.666 to one decimal place we raise the first digit after the decimal point if its successor is more than or equal to five. In this case the successor is 6 therefore 30.666 rounded up to one decimal place is 30.7.if the successor is below five,e.g.30.635,we round down the number to 30.6
- 12. Accuracy of Information: The accuracy of the computer output is critical. As the saying goes garbage in garbage out (GIGO),the accuracy of the data entered in the computer directly determines the accuracy of the information given out. Some of the errors that influence the accuracy of data input and information output include • Transcription and Computation errors
- 13. Electronic Data Processing Methods There are several ways in which a computer, under the influences of an operating system is designed to process data. 1. Online processing 2. Real time processing 3. Distributed processing 4. Time sharing 5. Batch processing 6. Multiprocessing 7. Multitasking 8. Interactive processing
- 14. Online processing: In online data processing data is processed immediately as it is received. The computer is connected directly to the data input unit via a communication link. The data input may be a network terminal or online input devices attached to the computer. Real-time processing: Computer processes the incoming data as soon as it occurs, updates the transaction file and gives an immediate response that would affect the events as they happen. This is different from online in that for the latter an immediate response may not be required. • The main purpose of a real-time processing is to provide accurate, up-to-date information hence better services based on a true (real) situation. • An example of a real time processing is making a reservation for airline seats. A customer may request for an airline booking information through a remote terminal and the requested information will be given out within no time by the reservation system. If a booking is made, the system immediately updates the reservation file to avoid double booking and sends the response back to the customer immediately.
- 15. Distributed data processing: refers to dividing (distributing) processing tasks to two or more computer that are located on physically separate sites but connected by data transmission media. Multiprogramming: Where a distributed database will have different tables of the same database residing on separate computers and processed there as need arises. Time sharing: Where many terminals connected to a central computer are given access to the central processing unit apparently at the same time. However in actual sense, each user is allocated a time slice of the CPU in sequence. Batch processing: Data is accumulated as a group (batch) over a specified period of time e.g. daily, weekly or monthly. The batch is then processed at once. For example in payroll processing system.
- 16. Class Activity 1. What is a Data Processing cycle? 2. List the various steps in the data processing cycle and briefly describe what happens at each stage. 3. Identify two types of processing errors and discuss how they may affect the information produced as output.