DATA PROCESSING
Introduction 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, on the other hand, refers to the meaningful output obtained after processing the data. Therefore the data processing refers to the process of transforming raw data into meaningful output i.e. information. Data processing can be done manually using pen and paper, mechanically using simple devices like typewriters or electronically using modem data processing tools such as computers. Electronic data processing has become so popular that manual and mechanical methods are being pushed to obsolescence. Data processing cycle Data processing cycle refers to input-process-output stages that data goes through to be transformed into information. It is often referred to as a cycle because the output obtained can be stored after processing and may be used in future as input. The four main stages of data processing cycle are: Data collection Data input Processing Output Data collection Data collection is also referred to as data gathering or fact-finding. It involves looking for crucial facts needed for processing. Methods of data collection Some methods of data collection include interviews, use of questionnaires, observation etc. In most cases, the data is collected after sampling. Sampling is the process of selecting representative elements (e.g. people, organisations) from an entire group (population) of interest. Some of the tools that help in the data collection include source documents such as forms, data capture devices such as a digital camera etc. Stages of data collection The process of data collection may involve a number of stages depending on the method used. These include: Data creation: This is the process of putting together facts in an organised format. This may be in form of manually prepared document or captured from the source using a data capture device such as a bar code reader. Data transmission: This will depend on whether data need to be transmitted via communication media to the central office. Data preparation: This is transcription (conversion) of data from source document to machinereadable form. This may not be the case for all input devices. Data collected using devices that directly capture data in digital form do not require transcription. Media conversion: Data may need to be converted from one medium to another e.g. from a floppy disk to 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 at the input. Sorting: In case the data needs to be arranged in a predefined order, it is first sorted before processing. Data input Data input refers to a process where the collected data is converted from human readable form to machine-readable form (binary form). The conversion takes place in the input device. Processing This is the transformation of input data by the central processing unit (CPU) to a more meaningful output (information). Some of the operations performed on data include calculations, comparing values and sorting. Output The final activity in data processing cycle is producing the desired output also referred to as information. The information can then be distributed to the target group or stored for future use. Distribution is making the information available to those who need it and is sometimes called information dissemination. This process of dissemination may involve electronic presentation over radio or television, distribution of hard copies, broadcasting messages over the Internet or mobile phones etc. Description of errors in data processing The accuracy of computer output is very 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, computation and algorithm errors. Transcription errors Transcription errors occur during data entry. Such errors include misreading and transposition errors. Misreading errors Incorrect reading of the source document by the user and hence entering wrong values bring about misreading errors. For example, a user may misread a hand written figure such as 589 and type S86 instead i.e. confusing 5 for S. Transposition errors Transposition errors results from incorrect arrangement of characters i.e. putting characters in the wrong order. For example, the user may enter 396 instead of369. Transcription errors can be avoided by using modem data capture devices such as bar code readers, optical character readers, and digital cameras etc., which enter data with minimum user intervention. Computational errors Computational errors occur when an arithmetic operation does not produce the expected results. The most common computation errors include overflow, truncation and rounding errors. Overflow errors An overflow 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 Truncation errors result from having real numbers that have a long fractional part that 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. The resulting number is not rounded off. Rounding errors 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 5. In this case, the successor is 6 therefore 30.666 rounded up to one decimal place is 30.7. If the successor is below 5, e.g. 30.635, we round down the number to 30.6. Algorithm or logical errors An algorithm is a set of procedural steps followed to solve a given problem. Algorithms are used as design tools when writing programs. Wrongly designed programs would result in a program that runs