2. Information Processing

3. Content covered  Data and information  Information Qualities  Data/Information Processing  Commercial Information Processing  Industrial Information Processing  Scientific Data Processing  Information Retrieval and Management  Sources of data  Data Integrity  Verification  Validation

4. Data and information Data is the raw materials that is input into a computer system. It consists of characters, numbers and program code. Information is data that has been processed by a computer system

5. Data and Information How are data and information related? p. 514 Fig 10-1 Next processing data stored on disk Step 1. The member data, including a photograph, is entered and stored on the hard disk. Step 2. The computer extracts the member data from disk. Step 3. The receipt is created and printed.  Data is raw facts  Information is data that is organized and meaningful receipt  Computers process data into information

6. Useful Accessible Organized Information Qualities What are the qualities of valuable information? p. 516 - 517 Next Timely Verifiable Accurate Cost-effective

7. Information Qualities  Accurate information is error free. Inaccurate information can lead to incorrect decisions.  Verifiable information can be proven as correct or incorrect.  Timely information has an age suited to its use. Most information loses value with time.

8. Information Qualities  Organized information is arranged to suit the needs and requirements of the decision maker.  Accessible information is available when the decision maker needs it. Having to wait on information may delay important decision.  Useful information has meaning to the person who receives it.

9. Information Qualities  Cost-effective information should give more value than it costs to produce.

10. Data/Information Processing Information (or data) processing refers to computer-based systems that take in data and generate information

11. Information Processing There are many ways in which data can be processed to become information. Here are some of them:  Carrying out calculations in a spreadsheet  Printing a document or image  Displaying an image on the screen  Updating data in a file.  Sorting data into alphabetical order.

12. Commercial data processing Computer systems are used in many businesses to carry out some time-consuming administrative tasks. Examples:-  Payroll – calculating employees pay  Orders – recording orders placed by customers  Sales – in a shop, dealing with purchases at the till  Invoices – sending request for payment to customers  Accounts – keeping track of receipts and payments  Marketing – designing packaging and advertising  Correspondence – sending letters and emails

13. Industrial data processing Industrial and manufacturing businesses need to carry out all the business task. In addition, they have further use for data processing such as:  Control systems – controlling the processes used when manufacturing products  Computer Aided Design – designing products  Computer Aided Engineering – using special software  Computer Aided Manufacture – using special software to develop and test products

14. Control systems We can use information processing systems to control machines automatically. Here are some examples:-  Factories are often largely automated, e.g. manufacturing chemicals, packaging goods.  The signalling systems on many railways across the world are controlled by computers, to ensure that the trains pass safely

15. Control systems  Some factories use robots to manufacture goods, such as automobiles.  Most electronic equipment in the home has some element of computer control, e.g. VCR’s, digital televisions, digital cameras, microwave oven, washing machines, cell phones

16. Control systems They are two main types of control system:  Automation systems – these are straightforward type of control system in which tasks are carried out automatically. For e.g. running a washing machine.  Process control systems – these are a type of control system used in manufacturing in which actions are changed depending on feedback from sensors. A sensor can measure things like temperature, humidity, light, sound, movement and pressure.

17. Scientific data processing Scientist can gather a lot of data during an experiment. Sometimes they will use sensors to capture data over a period of time. In other experiments the scientist themselves may be recording readings on a source document.

18. Information Retrieval When data stored on a computer system is searched and the relevant information is found, this is known as information retrieval.

19. Information management Information management ensures that all data is input accurately, stored correctly, retrieved easily and output in a way that provides useful information.

20. SOURCES OF DATA Source Document Human Readable Machine Readable Turnaround Document

21. Source Documents v A source document is the original form or paper from which data was taken. Examples of source documents time cards, order forms, invoices, pay cheques, brochures, photographs, inventory tags etc.

22. Human Readable v Human readable language refers to a language that a human can fully read and understands. For example the language of origin (whether English, Spanish or French) of an individual or a language learnt along the path of life.

23. Machine Readable  Machine readable language is the language that the computer understands. For example information read from a storage device.

24. Turnaround Documents vAvA turnaround document is a document that you return to the company that creates and sends it. For example electricity bills, water bills, telephone bills etc. The customers normally tear off a portion of the bill and send it back with the payment.

25. Data Integrity What is data integrity? p. 516 Next  Degree to which data is correct  Garbage in, garbage out (GIGO)—computer phrase that means you cannot create correct information from incorrect data Garbage out Garbage in Data integrity is lost

26. Data Verification Data verification is the process by which an individual checks to ensure that the information keyed in by another person is correctly entered into a computer system. Data verification is a process carried out by humans.

27. Data Verification errors Two common errors:- Typographical errors Transpositional errors

28. Data Verification methods  Proofreading – checks the data entered against the data on the original source document. The person entering the data reads the source document and checks that it matches what he or she entered into the computer.

29. Data Verification methods (cont’d)  Double-entry – is where the same data is entered twice, sometimes by different people. If the data differs between the two entries, it does not get processed. It can be expensive and time-consuming to use this method, but it does ensure very accurate data capture.

30. Validation What is validation? p. 522 Fig. 0-8 Next  Process of comparing data with a set of rules to find out if data is correct.  Data validation is an automatic process carried out by software.  Reduce data entry errors and enhance data integrity before program writes data on disk.

31. Types of Data Validation  Range checks – ensures that numbers entered fall within a specific range. If someone enters 25 hours in a day that will not be calculated.  Data type checks – ensures that the right type of data has been entered. You do not type letters in a telephone numbers.

32. Types of Data Validation (cont’d)  Consistency checks – compares data you have entered against other data you have entered. If you enter a person’s year of birth and their age in separate fields, a consistency check will ensure that the two fields correspond with each other.

33. Types of Data Validation (cont’d)  Reasonableness checks - ensures that the data is reasonable – not completely unrealistic. If you are entering salary information into a payroll system, a reasonableness check will ensure that you do not enter extra zeros (0’s) by mistake.

34. Verification Vs. Validation  Verification is the process of determining the correctness of the data. (e.g. Was this done right or not?) { Verification is a Preventive process/actions, which makes it a QA process } Testing against specifications.  Validation is the process of determining if the data is correct. (e.g. Was this the right thing to do or not?) { Validation is a Corrective process/actions, which makes QC process} Testing against requirements

35. Verification Vs. Validation  Validation is the checking of data before processing to ensure that it is acceptable for it or not. E.g. When entering a date, the validation for month is 1-12, you cannot enter 13, its out of range. Similarly a telephone number cannot contain letters.  Whereas Verification is the checking of data that has been copied from one place to another to ensure that is replaces the original one. E.g. PASSWORD. When you sign up in a site, just like WIKIANSWERS, you have to enter your password twice, the second entry being compared with the first.

36. End of presentation Thank you for your undivided attention