1. DATA RECORDS & FILES
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2. Data -These are raw facts and figures.
For example, data can be, recorded hours worked by an employee, invoices, receipts, orders numbers, or prices, goods quantities
Data itself is meaningless unless manipulated and transformed (processed) into meaningful forms (information)
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3. Data processing stages
Data processing stages refers to the process of collecting data, at the point of activity up to the time data is transformed into information.
Raw data is assumed to pass through 5 stages as shown below.
OUTPUT
INPUT
PROCESS, storage
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4. By Sinkala

5. Sources of Data (origination)
Data can originate from the following sources:
-Business transactions(invoices, receipts, customer orders etc)
-Census( counting of people and distribution of wealth)
-Observation(observing some happenings and recorded details)
-Experiments (observations and recordings about the progress of an experiment)
- Market survey(sampling to test the reaction of a product or service being introduced)
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6. Verification(Preparation)
Data verification is a process of checking for errors in input data before it is carried forward for processing.
Verification is normally carried out by more than one person or machine.
The same data is compared and checked character by character against one another

7. Types of Errors detected by verification
-Transcription errors
-Transposition
-Omission

8. Six (6) Steps required to process a transaction and they include( refer to slide 4 )
data entry/ capture
validation
DATA PROCESSING
storage
OUTPUT generation
query support

9. Data entry/ capture
This is the collection of raw data from the outside world into an information system. It can be manually or by using automatic data capture devices, such as:
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10. MICR,
OCR,
OMR,
Bar Code Reader 
Keyboard, mouse, flatbed scanners, joysticks, digital data tablets (for graphic drawing), electronic cash registers etc

11. Validation
Validation is ensuring that the input data is of the right type and within reasonable limits.
Type of validation checks.
(concept of a field)

12. E. g name, a date, an amount, sex etc NAME: SEX: COURSE:
A field is any item of data within a record. It is made up of a number of characters.
E. g name, a date, an amount, sex etc
NAME:
SEX:
COURSE:
NAME
SEX
COURSE

13. Type of validation checks.
Size checks. - Fields are checked to ensure that they contain the right number of characters e.g. customer No. Specified as 6 numerical characters. This means that the program will validate for 6 numerical characters.
Presence check
Range checks also called limit checks
Character check
Format check.
Consistency

14. PROCESSING
This is a procedure of transforming raw data into useful information. Therefore, at this stage DATA is converted into INFORMATION.
(Information is the processed data)

15. PROCESSING
This is a procedure of transforming raw data into useful information. Therefore, at this stage DATA is converted into INFORMATION.
(Information is the processed data)
STORAGE
After data has been processed, it is stored either internally or externally.
Typical storage devices (magnetic and optical) include:
Magnetic: hard disk (fast access, big capacity)
-floppy disk (slow access, low capacity)
-Flash disk, Tapes
Optical: CDs, DVDs
With storage the main features include speed, reliability and capacity of storage.

16. OUTPUT
Is the final generation of information from an information system to the outside world.
Output generation is facilitated by output devices which include:
-CRT (cathode ray tube) monitors and LCD/LED displays
-printers
-speakers
-plotters
QUERY SUPPORT
At this stage information is queried for further verification or for conformity (agreeing with certain accepted standards or norms).

17. General Qualities of good information:
For information to be useful, it must possess several characteristics attributes. These attributes add value or increase the potential of information.
Accurate
Meaningful
Reliable/ reliability
Easy to use
User targeted
Relevant
Timely
Complete
Error free
verifiable

18. General Qualities of good information:
Accurate- For information to be useful, it must be exactly and precise. This can help the decision makers to make accurate decisions.
Meaningful- Good information must be meaningful and easy to understand, not to be misleading.
Reliable- Good information must accurately represent the events or activities of an organization. In addition, it must be easy to follow and retrievable.

19. General Qualities of good information:
Easy to Use-(Understandable) - Good information must be user friendly. Information must not be complicated because it may not be too useful as people may not really understand it.
User Targeted- information must be specific, brief and user targeted.
Timely- Good information should provided in good time and received at the right time

20. General Qualities of good information:
Relevant –good information should make a difference to the decision maker by reducing uncertainty or by adding increased knowledge or value to the decision maker.
Complete- must include all relevant data or aspects of the data that are required.
Error free- data sets must contain a minimum number of errors.
Verifiable- generated information of the same process must be the same or within reasonable variance.

21. Data organization c c c c c c c c
Refers to the way we store and arrange data, in order to make it easy for storage, manipulation and retrieval of information. Information is organized in unit form according to the data hierarchy structure shown below
FILE
RECORDS
RECORDS
RECORDS F F F
FIELD F F
FIELD
FIELD
FIELD c c c c c c c c

22. A FILE:

23. Exercise(max 10min)
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