Information Technology Data Processing Prof. Adnan Khalid.

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Presentation transcript:

Information Technology Data Processing Prof. Adnan Khalid

Data Processing Data processing (DP) is any computer process that converts data into information or knowledge. The processing is usually assumed to be automated and running on a computer. Because data are most useful when well-presented and actually informative, data-processing systems are often referred to as information systems to emphasize their practicality.computer processdatainformationknowledge computerinformation systems

Data/Information Processing Cycle All data and information processing goes through stages in a logical order. You need to know what each step means, how it differs from other steps, and what sorts of processes and equipment is relevant to each step. Note that the stages below do not have to be in this order, not all steps must be carried out, and some steps may be repeated. All data and information processing goes through stages in a logical order. You need to know what each step means, how it differs from other steps, and what sorts of processes and equipment is relevant to each step. Note that the stages below do not have to be in this order, not all steps must be carried out, and some steps may be repeated.

Stages of the Information Cycle Input Input Acquisition Acquisition Validation Validation Encoding Encoding Processing (manipulation) Processing (manipulation) Sorting Sorting Calculations Calculations Summarizing Summarizing Classification Classification Storage Storage Output Output Retrieval Retrieval Decoding Decoding Communication Communication Feedback Feedback

The Input Phase Putting the acquired data into the information system. Examples: typing the hours from the timecards into a spreadsheet. scanning the survey cards with a card reader typing jokes into a word processor Typical input devices: keyboards, mice, flatbed scanners, bar code readers, joysticks, digital data tablets (for graphic drawing), electronic cash registers.

Acquisition The collection of raw data from the outside world so it can be put into an information system. Note the difference between acquisition and input. Examples: Doris, the pay clerk, going to the factory's foremen and collecting the workers' timecards so she knows how many hours each person worked that week. Conducting a survey of customer's opinions. Collecting jokes for a joke book. Using a form on a website to collect visitors' opinions

Validation Checking the quality of the data before it is processed. Remember GIGO: garbage in, garbage out. Processing rubbish data gives rubbish information. If all the foremen in the factory just made up the numbers on the workers' time cards, working on the pay cheques would be totally pointless. Validation is ensuring inputted data is of the right type (e.g. numeric) and within reasonable limits (e.g. ages between 1 and 130). Databases and spreadsheets can have validation rules built into data fields to reject impossible entries. Validation can include: Existence: is some essential data simply missing, such as a name? Reasonableness: does it seem logical? Checking hours are within reasonable limits (e.g. anything over say 50 hours a week may be questioned) Consistency: Checking for inconsistencies in surveys (e.g. a person claims to be unemployed but earns $80,000 a year.) Some surveys ask similar questions in different parts of the survey to check whether people are lying when they answer.

Validation Vs Verification Verification is the process of entering data twice, and comparing the two entries to find differences. Aa common example of this is when you are asked to enter a new password twice to ensure it has been entered accurately.

Encoding Data is converted into computer understandable format. Data is converted into computer understandable format. Computer can understand digits only so the data can only be encoded into digital format. Computer can understand digits only so the data can only be encoded into digital format.

Processing This is a key point. At this stage DATA is converted into INFORMATION. e.g. a thousand surveys are converted into a graph that actually means something to a person. Examples: Calculating wages from hours worked Counting the number of male and female responding to the survey Sorting jokes alphabetically by topic Typical processing software includes word processors, spreadsheets, databases, payroll systems, web browsers that decode and present HTML pages and compressed images.

Storage Unless you want to input the data every time you process it, it's sensible to store the data. You also may want to store information you have produced so you don't have to keep repeating work. Typical storage devices: hard disk (fast, big capacity) Floppy disk (slow, low capacity) writeable CD-ROM QIC (quarter inch cassette tape) EPROM (Electronically programmable ROM), flash RAM (memory chips that keep their contents after the power is turned off e.g. memory sticks, BIOS chips). Issues include speed, reliability and capacity of storage.

Output All the previous steps are useless unless you can see the results. Devices include: CRT (cathode ray tube) monitors and LCD displays printers sound cards/speakers plotters special purpose displays (e.g. the floor indicator in a lift)

Retrieval The reverse of storage. There's not much point storing data and information unless you can retrieve it again later. Issues include speed and reliability of retrieval.

Decoding Information must be decoded and presented into human / user understandable form. The Information is converted into text or visuals to make it easy for humans to understand.

Communication Sending data or information to another place. This usually involves LANs (local area networks), WANS (wide area networks - LANs joined together), and the internet. Typical devices are the modem, network cabling, hubs, switches, satellites, microwave links, infrared links, radio networking, fiber optic cable, routers.modemhubs, switchesradio networking fiber optic cable

Feedback Feedback involves evaluating the output and adjusting the input or the processing phase accordingly to make the output appropriate.