The document outlines the objectives and operations involved in data processing, defining data as raw facts that require manipulation to become useful information. It describes the data processing cycle, including steps such as recording, verifying, duplicating, classifying, sorting, calculating, summarizing, merging, storing, retrieving, and providing feedback. Additionally, it covers methods of processing data, including batch, online, real-time, and distributed processing.

1. DATA PROCESSING

2. OBJECTIVES:
1. Define what is Data processing
2. Categories of Data Processing
3. Identify the Operations and Methods of data
processing

3. DATA PROCESSING
 Data is defined as a collection of raw and unprocessed facts. Since it is
still raw, it needs to be seamed to other data. The data must be
manipulated and processed to achieve a desirable result and turn it into
more useful information. Score in quizzes, student names, sale figures,
grade reports and others are all examples of data. After data have been
processed they can now be considered as information. It is the output of
data that has been already manipulated and transformed into something
useful.

4. Unorganized Facts
No. of hours rendered, other
deduction
No. of items and cost
Cost per subject and other
Miscellaneous
Useful Information
Payroll reports
Sales Report
Registration Form

5.  Data Processing is a process of manipulating data to
make it more useful forms. It does not only consist of
mathematical calculations but also data operations. The
term data processing is a cumulative technique for the
collection of data to acquire certain objectives.

6. DATA PROCESSING CYCLE

7. EXPANDED DATA PROCESSING CYCLE

8. DATA PROCESSING OPERATION
 RECORDING –refers to the transfer of data from one form to
another. Numbers or figures and facts resulting from the operation
are documented.
 VERIFYING – refers to the checking of data for any errors or
discrepancy because most data are recorded manually.
 DUPLICATING – is the reproduction of data into many forms.
 CLASSIFYING – it separates data into its distinctive categories

9. DATA PROCESSING OPERATION
Recording
1: Writing down a customer's order details from a phone call
onto a paper form.
2: Entering a patient's vital signs into an electronic health
record system.

10. DATA PROCESSING OPERATION
Verifying
1: Double-checking a written sales receipt against the actual
purchased items to ensure accuracy.
2: Reviewing a manually entered attendance sheet to confirm
that all names and times are correctly recorded.

11. DATA PROCESSING OPERATION
Duplicating
1: Making photocopies of a printed financial report to distribute
to different departments.
2: Saving a digital document in multiple file formats (e.g., PDF,
Word) for different uses.

12. DATA PROCESSING OPERATION
Classifying
1: Sorting books in a library into categories such as fiction,
non-fiction, and reference.
2: Organizing emails into folders based on topics like work,
personal, and spam.

13. DATA PROCESSING OPERATION
 SORTING – refers to the arranging of data in specific order.
Orders may be cardinal, ordinal, alphabetical or
lexicographic order.
 CALCULATION – refers to the arithmetic calculation of data.
 SUMMARIZING and REPORTING – the data are condensed
to their meaningful forms.

14. DATA PROCESSING OPERATION
 Sorting
• 1:Arranging a list of employee names in alphabetical order for a
directory.
• 2: Sorting a stack of invoices by date before filing them.

15. DATA PROCESSING OPERATION
Calculation
1:Adding up all sales figures from a day's transactions to get the
total revenue.
2: Calculating the average test score for a class of students.

16. DATA PROCESSING OPERATION
 7. Summarizing and Reporting
• 1: Condensing a month's worth of sales data into a one-page
summary report.
• 2: Creating a summary of customer feedback from surveys for a
management meeting.

17. DATA PROCESSING OPERATION
 MERGING – is the putting together of two or more sets of data
with the same key to be one set of data.
 STORING – is the saving of data into files for future reference.
 RETRIEVING – refers to the recovering of stored data and/or
information when needed.
 FEEDBACK – is the operation that compares the result to the
objectives set.

18. DATA PROCESSING OPERATION
 . Merging
 Example 1: Combining two customer databases from
different branches into one unified database.
 Example 2: Merging data from multiple Excel sheets
into a single consolidated sheet.

19. DATA PROCESSING OPERATION
 9. Storing
 Example 1: Saving completed project files into a
designated folder on a computer for future reference.
 Example 2: Filing paper receipts in a filing cabinet
organized by month.

20. DATA PROCESSING OPERATION
 10. Retrieving
 Example 1: Searching for and opening a stored
document on a computer when it's needed for a
meeting.
 Example 2: Looking up a client’s file in a physical
filing system to retrieve their contact information.

21. DATA PROCESSING OPERATION
 11. Feedback
 Example 1: Comparing monthly sales results against
targets and making adjustments to the sales strategy.
 Example 2: Reviewing student performance on a test
to identify areas where the teaching method may need
improvement.

22. Identify what kind of Data
Processing operation take place in
the following sentences.

23. The Bank manager is imposing a
10% interest rate on the new salary
loan to every account in the BPI
Family Bank.

24. Emmanuel found the LACTUM 3+
for kids in the lane F, which is
under the Dairy Product.

25. The students of grade 7 is make a
line up according to height.

26. John recovered the saved file after
the unexpected power interruption.

27. Nathalie, a secretary in court, is
jotting down notes in stenography
for the court’s minute.

28. The Jollibee customer answers the
survey form for new product offered
by the establishment.

29. Mr. Salazar, a Mathematics
teacher, found out that there are
some errors in his class record.

30. Grade 9 and the Grade 10 students
will be the new seminar committees
on “Students Symposium.”

31. Mrs. Santos student’s in English
communication, were asked to submit a
reaction paper on the issue about the
effect of this PANDEMIC on the
Education System of the Philippines.

32. Jayson requested for another copy of his
Form 138 at Cayetano Arellano High
school as requirement for the application
of Entrance Examination at UPCAT.

33. GROUP ACTIVITY:
Give one example for each data
processing operation.

34. METHODS OF PROCESSING DATA
1. Batch Processing. This applies serial processing. In this
method, the data are being collected into a certain groups or
batches to permit convenience, efficiency following a step by step
procedure.
2. On-line Processing. It is a method where all the information and
devices are under the direct control of the central processing unit of
a computer that permits sharing of files and devices with all
computers that are connected to the server.

35. METHODS OF PROCESSING DATA
3. Real-time Processing. It is a method that provides a fast response to
inquiry and processing. It processes the data as soon as data have been
inputted and has the capability of the outcome of the activity or process in a
matter of seconds or even milliseconds.
4. Distributed Processing. It is the most complicated level of computer
processing. It is usually consists of different computers that are connected to
a large central computer system or server to help the user conduct inquiries,
processes, or other data processing operations locally or even globally.

36. ACTIVITY

37. GROUP 1: BATCH PROCESSING
• Scenario: A utility company processes monthly billing
statements for its customers.The company collects usage data
throughout the month and processes all the bills at once in a
batch at the end of the billing cycle.This allows the company to
efficiently calculate charges, apply discounts, and generate
invoices for thousands of customers simultaneously.

38. GROUP 2: ON-LINE PROCESSING
• Scenario: An e-commerce website handles multiple
transactions at once.When a customer places an order, the
system immediately checks the availability of the item,
processes the payment, updates the inventory, and confirms the
order.All these operations happen in real-time while the
customer is still online, ensuring that stock levels are accurate
and orders are processed promptly.

39. GROUP 3: REAL-TIME PROCESSING
• Scenario: A medical emergency response system processes
incoming calls and dispatches ambulances.When a call is
received, the system immediately processes the caller’s location,
checks for available ambulances, and dispatches the closest one.
The system must provide immediate responses and updates to
ensure that the emergency services arrive as quickly as
possible.

40. GROUP 4: DISTRIBUTED PROCESSING
• Scenario: A global airline uses a distributed processing system to
manage flight bookings. Different regional offices handle local flight
reservations, updates, and cancellations.All these local systems are
connected to a central server that synchronizes the data, allowing
customers and staff to access the latest information on flights and
bookings from anywhere in the world.This system allows the airline
to manage a large volume of data across multiple locations efficiently

41. CONCLUSION
Data processing involves three steps, the
input, process and output. The main goal of
data processing is to process data into a more
useful form which could use by people into a
more meaningful form called information.