3.1 Data and Information –The rapid development of technology exposes us to a lot of facts and figures every day. –Some of these facts are not very meaningful to us. We have to process them properly before they become useful for us. –Data –A collection of unorganized facts and has no meaning on its own –In the form of numbers, characters, symbols, audio, graphics or video clips, etc. –Information –the processed data which has a specific meaning, and it is useful for decision making.

Imagery of data (left) and information (right) Data is processed into information. 3.1 Data and Information Peter Mary Jeff John May NameAgeHeight/cm Jeff16169 John18177 Mary17165 May17160 Peter17170 Process DataInformation

Imagery of data (left) and information (right) Data is processed into information. 3.1 Data and Information Peter Mary Jeff John May NameAgeHeight/cm Jeff16169 John18177 Mary17165 May17160 Peter17170 Process DataInformation

–Common types of data processing: Searching Calculation Sorting Deleting Inserting Updating 3.2 Data Processing

Sales record CodeProductJanuaryFebruaryMarch 1 Cooker Cooker hood Sterilizer Stainless steel wok Fan Quarterly sales record from January to March

Searching –Look up specific information from a database based on certain criteria. –e.g. If we want to find the sales of ‘Fan’ in January, a possible way is to examine the column ‘Product’ until we see the product name ‘Fan’. –When the record is located, the sales of ‘Fan’ in January can be found in the third column ‘January’. 3.2 Data Processing

Calculation –Mathematical manipulation of data to produce other useful information such as total and average. –The following shows the formula to calculate the first- quarter total sales and the monthly average sales for each product: first-quarter total sales = sum of sales in January, February and March monthly average sales = first-quarter total sales / Data Processing

Calculation 3.2 Data Processing CodeProductJanuaryFebruaryMarchTotalAverage 1Cooker Cooker hood Sterilizer Stainless steel wok Fan Sales record from January to March with the result of calculation

Sorting –The rearrangement of records, which is a row of a table, according to a specific criterion. –e.g. We want to sort the records in a descending order of the average monthly sales. –In this case, the average sale is used as the sort key. –The value of a sort key is used as a reference in rearranging records in a sorting process. 3.2 Data Processing

Sorting 3.2 Data Processing CodeProductJanuaryFebruaryMarchTotalAverage 4Stainless steel wok Cooker hood Cooker Sterilizer Fan Sorted sales record

Deleting –The removal of a record from the table. –e.g. The sales record for the ‘Fan’ is known to be taken from a wrong source. –The record should be removed from the table. 3.2 Data Processing CodeProductJanuaryFebruaryMarchTotalAverage 4Stainless steel wok Cooker hood Cooker Sterilizer The sales record of ‘Fan’ is deleted.

Inserting –Adding a new record to the existing table. 3.2 Data Processing CodeProductJanuaryFebruaryMarchTotalAverage 4Stainless steel wok Cooker hood Cooker Heater Sterilizer A sales record ‘Heater’ is inserted.

Updating –Modifying the data of existing records. –e.g. The product code for ‘Cooker’ should be ‘10’. The product code is updated from ‘1’ to ‘10’. 3.2 Data Processing CodeProductJanuaryFebruaryMarchTotalAverage 4Stainless steel wok Cooker hood Cooker Heater Sterilizer A sales record ‘Cooker’ is updated.

Updating –Modifying the data of existing records. –e.g. The product code for ‘Cooker’ should be ‘10’. The product code is updated from ‘1’ to ‘10’. 3.2 Data Processing CodeProductJanuaryFebruaryMarchTotalAverage 4Stainless steel wok Cooker hood Cooker Heater Sterilizer A sales record ‘Cooker’ is updated.

–The accuracy of the inputted data determines the quality of the output of data processing. –If the data entered is incorrect or incomplete, the program will not generate useful result. This principle is known as garbage-in-garbage out (GIGO). –Two methods used to reduce errors of inputted data: –data validation –data verification 3.3 Correctness of Data

Data Validation –The process of checking data with a set of rules or values to make sure that the data entered are reasonable and valid. –This is usually done by the program which validates data in the data entry screen. –Common types of data validation: Range check Format check

3.3 Correctness of Data Range Check –Ensure that the value of inputted data falls within a valid range. –In the above example, the age entered must be between 18 and 55. An example of applying data validation: filling an online registration form Range check Format check Data validation

3.3 Correctness of Data Format Check –Ensure that the inputted data is of a certain type or pattern. –In the above example, user ID should consist of alphabets, numbers or a mixture of them.

3.3 Correctness of Data Data Verification –A measure to check whether the inputted data matches with that in the source document –This measure is carried out manually. –Examples: Confirmation Inputting data twice

3.3 Correctness of Data Confirmation –Ask users to check manually whether the inputted data is free of error. –e.g. After a user enters data for the creation of a new account, the program will display a confirmation window to display the inputted data. –The user is asked to confirm that the data entered is correct by clicking. Confirm A window displaying entered data for confirmation

3.3 Correctness of Data Inputting Data Twice –Inputting data twice is to ask users to enter the data twice. –The computer system then checks the second entry against the first one. –It reports any discrepancies and the user is required to correct the error manually. Password is entered twice to verify the inputted data.

3.3 Correctness of Data Inputting Data Twice –Inputting data twice is to ask users to enter the data twice. –The computer system then checks the second entry against the first one. –It reports any discrepancies and the user is required to correct the error manually. Password is entered twice to verify the inputted data.

3.4 Types of Data Processing Batch Processing –The computer does not process data immediately after it is entered. –Data and jobs are accumulated. A batch file is created to instruct the computer when and how to carry out the jobs. –The computer processes the accumulated data and jobs as instructed automatically at a specified time.

3.4 Types of Data Processing Batch Processing –Examples: Print monthly bank statements. Calculate examination results. Back up files stored on a server. Monthly bank statementsExamination result

3.4 Types of Data Processing Real-time Processing –A mode of operation that the program allows a job to be handled as fast as possible upon request. –Any data entered is immediately processed to produce output, which is then fed back to users. –The response time is short and the information is always updated.

3.4 Types of Data Processing Real-time Processing –Examples: Online ticketing system ATM system Online ticketing system ATM system

3.4 Types of Data Processing Real-time Processing –Examples: Online ticketing system ATM system Online ticketing system ATM system