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.
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 - PowerPoint PPT Presentation
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
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
17 17 16 18 17
167 165 169 177 160
Peter Mary Jeff John May
Name Age Height/cm
Jeff 16 169
John 18 177
Mary 17 165
May 17 160
Peter 17 170
Process
Data Information
Imagery of data (left) and information (right)
Data is processed into information.
3.1 Data and Information
17 17 16 18 17
167 165 169 177 160
Peter Mary Jeff John May
Name Age Height/cm
Jeff 16 169
John 18 177
Mary 17 165
May 17 160
Peter 17 170
Process
Data Information
– Common types of data processing:SearchingCalculationSortingDeletingInsertingUpdating
3.2 Data Processing
3.2 Data Processing
Sales record
Code Product January February March
1 Cooker 78 95 85
2 Cooker hood 83 83 98
3 Sterilizer 71 80 89
4 Stainless steel wok
90 93 96
5 Fan 85 75 77
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 Marchmonthly average sales = first-quarter total
sales / 3
3.2 Data Processing
• Calculation3.2 Data Processing
Code Product January February March Total Average
1 Cooker 78 95 85 258 86
2 Cooker hood 83 83 98 264 88
3 Sterilizer 71 80 89 240 80
4 Stainless steel wok
90 93 96 279 93
5 Fan 85 75 77 237 79
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
• Sorting3.2 Data Processing
Code Product January February March Total Average
4 Stainless steel wok
90 93 96 279 93
2 Cooker hood 83 83 98 264 88
1 Cooker 78 95 85 258 86
3 Sterilizer 71 80 89 240 80
5 Fan 85 75 77 237 79
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
Code Product January February March Total Average
4 Stainless steel wok
90 93 96 279 93
2 Cooker hood 83 83 98 264 88
1 Cooker 78 95 85 258 86
3 Sterilizer 71 80 89 240 80
The sales record of ‘Fan’ is deleted.
• Inserting– Adding a new record to the existing table.
3.2 Data Processing
Code Product January February March Total Average
4 Stainless steel wok
90 93 96 279 93
2 Cooker hood 83 83 98 264 88
1 Cooker 78 95 85 258 86
6 Heater 85 75 86 246 82
3 Sterilizer 71 80 89 240 80
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
Code Product January February March Total Average
4 Stainless steel wok
90 93 96 279 93
2 Cooker hood 83 83 98 264 88
10 Cooker 78 95 85 258 86
6 Heater 85 75 86 246 82
3 Sterilizer 71 80 89 240 80
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
Code Product January February March Total Average
4 Stainless steel wok
90 93 96 279 93
2 Cooker hood 83 83 98 264 88
10 Cooker 78 95 85 258 86
6 Heater 85 75 86 246 82
3 Sterilizer 71 80 89 240 80
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
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 checkFormat 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 statements Examination 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 systemATM system
Online ticketing system
ATM system
3.4 Types of Data Processing• Real-time Processing