This document provides an overview of data including definitions of key terms like data, information, primary and secondary data sources, qualitative and quantitative data, and discrete and continuous variables. It discusses the importance of data for decision making, problem solving, innovation and more. The evolution of data storage technologies from the 1960s to present is reviewed, from punch cards to modern cloud storage. Primary data sources include surveys, interviews, observations and questionnaires, while secondary data comes from published sources like books, journals, newspapers and websites.

1. Module 1:
DATA AROUND US

2. What is
DATA?
Image or icon

3. What is
DATA?

4. IMPORTANCE OF DATA

5. IMPORTANCE OF DATA
B C
A

6. IMPORTANCE OF DATA
E
D

7. IMPORTANCE OF DATA
Answers:
A. Innovation
B. Decision Making
C. Problem Solving
D. Personalization
E. Transparency and Accountability

8. EVOLUTION OF DATA STORAGE
1960 1965
Lots of master
files
- Complexity
of
Maintenance
&
Development
-
Synchronization
of data
-Hardware
“a single
source of
data for all
1970 1975
Database – Online,
high-
performan
ce
processing
1980
• The single-
database-
serving-all-
purposes
paradigm
• PC’s, 4GL
processing” transaction technology

9. EVOLUTION OF DATA STORAGE
1960s
Punch card
Magnetic tape
Disk drive

10. EVOLUTION OF DATA STORAGE
1960s
Tabulation
Machine

11. EVOLUTION OF DATA STORAGE
Mid - 1960s
Signetics 8-bit RAM

12. EVOLUTION OF DATA STORAGE
Mid-60’s Floppy disk
Disk drive
Transformer Read Only
Storage (TROS)

13. EVOLUTION OF DATA STORAGE
1960s

14. EVOLUTION OF DATA STORAGE
1970s
Hard Disk Drive
(HDD)
Micíopíoccsso
í
Optical
Storage

15. EVOLUTION OF DATA STORAGE
Mid-1970s
Laserdisc
Japanese
manufactured
dynamic
random-access
memory
(DRAM)
5.25-inch floppy disk
SRAM

16. EVOLUTION OF DATA STORAGE
1980s

17. EVOLUTION OF DATA STORAGE
1980s
IBM 3480 cartridge tape
system
3.5-inch floppy disks
CD-ROM

18. EVOLUTION OF DATA STORAGE
Mid-1980s
Redundant Array of Independent Disks

19. EVOLUTION OF DATA STORAGE
USB Flash drive
(2000) Cloud-based
network-attached
storage solutions
(2009)
Compact
Flash
(1994)

20. Data Source
A data source, in the context of
computer science and computer
applications, is the location
where data that is being used come
from. In a database management
system, the primary data source is
the database, which can be located
in a disk or a remote server.

21. THE DATA SOURCE
Internal
include data that exists
and is stored inside your
organization.
External
is data that was not
collected by your
organization
Sources
of Data

22. THE SOURCES OF DATA

23. KINDS OF DATA
PRIMARY DATA

24. SURVEY
Most
commonly
used method
in social
sciences,
management,
marketing and
psychology to
some extent
and can be
conducted in
different
methods.
This is a face-to-
face conversation
with the
respondent. It is
slow, expensive
and take people
away from their
regular jobs, but
this allow in-depth
questioning and
follow-up
questions.
EXAMPLES OF PRIMARY SOURCES OF DATA
INTERVIEW

25. QUESTIONNAIRE
Most commonly used
method in survey. These
are a list of questions
either an open-ended or
close-ended for whichIc
t
o
h
n
e
respondent give answers.
These can be conducted
via telephone, mail, live in
a public area, or in an
institute, through
electronic mail or through
fax and other methods.
These can be done while letting
the observing person know that
he is being observed or without
letting him know. These can
also be made in natural setting
as well as in artificially created
environment.
EXAMPLES OF PRIMARY SOURCES OF DATA
OBSERVATIONS

26. ADVANTAGES AND DISADVANTAGES OF PRIMARY DATA
ADVANTAGES OF
PRIMARY DATA
DISADVANTAGES OF
PRIMARY DATA

27. KINDS OF DATA
SECONDARY DATA

28. KINDS OF DATA

29. PUBLISHED
PRINTED SOURCES
EXAMPLES OF SECONDARY DATA
BOOKS
PUBLISHED
ELECTRONIC SOURCES
JOURNALS &
PERIODICALS
GENERAL
MAGAZINES & WEBSITES
NEWSPAPERS
E-JOURNALS WEBLOGS

30. ADVANTAGES AND DISADVANTAGES OF SECONDARY DATA
ADVANTAGES OF
SECONDARY DATA
DISADVANTAGES OF
SECONDARY DATA

31. Primary vs. Secondary Data
PRIMARY DATA SECONDARY DATA

32. Discipline Primary Secondary
Art 1) Article critiquing the work
Engineering Experimental data 2)
History
World War II personal
narrative
3)
Literature Shakespeare’s Hamlet 4)
Science 5)
Analysis of oceans’ changes
over the past 20 years
Theatre 6) Review of the performance
Psychology 7) Monograph on autism
Some comparative examples of primary and secondary sources:

33. Discipline Primary Secondary
Art Original artwork Article critiquing the work
Engineering Experimental data Journal article analyzing data
History
World War II personal
narrative
Book analyzing military
strategies of the War
Literature Shakespeare’s Hamlet
Critique and analysis of
characters in Hamlet
Science
Data reporting oceans’
temperature
Analysis of oceans’ changes
over the past 20 years
Theatre DVD of a performance Review of the performance
Psychology
Notes about a client with
autism
Monograph on autism
Some comparative examples of primary and secondary sources:

34. DATA TYPES
QUALITATIVE (CATEGORICAL) DATA

35. QUALITATIVE (CATEGORICAL) DATA
EXAMPLES:

36. QUALITATIVE (CATEGORICAL) DATA
EXAMPLES:

37. DATA TYPES
QUANTITATIVE (MEASUREMENT) DATA

38. QUANTITATIVE (MEASUREMENT) DATA
DISCRETE DATA CONTINUOUS DATA

39. QUANTITATIVE (MEASUREMENT) DATA
DISCRETE DATA
EXAMPLES:
CONTINUOUS DATA
EXAMPLES:

40. CONTINUOUS DATA
EXAMPLES:

41. CONTINUOUS DATA
EXAMPLES:

42. DATA
Quantitative data
Continuous
variable
Discrete
Attribute
Nominal
Ordinal
‘Open’
Qualitative data
Interval Ratio

43. Data Types Examples
•Blood pressure readings
•Number of optical shops in MM
Continuous Data
Discrete Data
•What was the severity of your flu?
•Low, Medium, or High
Ordinal Data
Nominal Data •Did you get a flu? Yes or No
•Please describe your hospital
experience.
‘Open Data’

44. Understanding Discrete vs. Continuous Growth
The key question: When does growth happen?
Discrete growth: change happens at specific intervals: eyeglass level
Continuous growth: change happens at every instant: bacteria colony

45. EXAMPLES OF CONVERSION OF
DISCRETE TO CONTINUOUS DATA
Measuring Attribute/Discrete Continuous
Gas Tank Empty/Full Gas Volume
Tree Heights Tall/Short Meters
Performance Poor/Average/Good Points/Pieces
Temperature # Days of Cold Average Temp.
Delivery No. of Late Time per Delivery
Scrap # of Pieces > Max Length Average Length

46. IMPORTANCE OF DATA
1. Improve People’s Lives
2. Make Informed Decisions
3. Stop Molehills From Turning Into
Mountains
4. Get The Results You Want
5. Find Solutions To Problems
https://www.c-q-l.org/resources/guides/12-reasons-why-data-is-important/

47. Difference between Data and Information

48. DATA VS. INFORMATION

49. COMPARISON CHART
BASIS FOR
COMPARISON
DATA INFORMATION
Meaning Unorganized information Processed data
What is it? It is just text and numbers. It is refined data.
Based on Records and Observations Analysis
Form Unorganized Organized
Useful May or may not be useful. Always
Specific No Yes
Dependency Does not depend on
information.
Without data,
information cannot be
processed.

50. DATA VS. INFORMATION

51. DATA VS. INFORMATION

52. DATA VS. INFORMATION

54. Examples of Data and Information
Data Information
1. The history of temperature readings all over
the world for the past 100 years
2. The number of visitors to a website by
country
3. The number of likes CEU has on Facebook
4. To create a NIC (National Identification
Card), first you get token/slip then take
pictures and step by step provide all the
details

55. Examples of Data and Information
Data Information
1. The history of
visitors to
past 100 years
2. The number of
website by country
Facebook
details
temperature 1. The data is organized and analyzed to
readings all over the world for the find that global temperature is rising.
a 2. Finding out that traffic in the Philippines
is increasing while that in Thailand is
decreasing.
3. The number of likes CEU has on 3. Demographic analysis of the data —
which age groups like CEU and where are
4. To create a NIC (National Identification they?
Card), first you get token/slip then take 4. They process all you’re details and
pictures and step by step provide all the issue you a card. And that card is the
information that you are a citizen of a
particular country.

56. CHAPTER 1: DATA AROUND US
References
Buendia, M. (2016). Introduction to Data Warehousing. Special Training in Business Analytics (Module 2) for Teachers of HEI
(pp. 1-5). Manila: University of the East.
Campaign, D. Q. (2011, June 24). Data Is Power. Retrieved from Youtube: https://www.youtube.com/watch?v=77UPUxB2b7o
Data vs. Information vs. Insight. (2018). Retrieved from Benedictine University:
https://online.ben.edu/programs/mba/resources/data-vs-information-vs-insight
Data, Information and Statistics. (2013, July 23). Retrieved from Statistics Canada: https://www.statcan.gc.ca/edu/power-
pouvoir/ch1/definitions/5214853-eng.htm
Donges, N. (2018, March 18). Data Types in Statistics. Retrieved from Towards Data Science:
https://towardsdatascience.com/data-types-in-statistics-347e152e8bee
Hinglish, T. (2018, January 22). What is Data | What is Information | Difference Between Data and Information. Retrieved
from Youtube: https://www.youtube.com/watch?v=F20qEwXBQaE
M, M. K. (2013, May 9). Source of Data in Research. Retrieved from SlideShare:
https://www.slideshare.net/manukumarkm/source-of-data-in-research
Roberts, T. (2015, December 6). Data vs. Information. Retrieved from YouTube:
https://www.youtube.com/watch?v=bitUrAmXTnI
Smith, P. (n.d.). Types of Data, Descriptive Statistics, and Statistical Tests for Nominal Data. Retrieved from University at
Buffalo: https://www.accp.com/docs/bookstore/biosampl.pdf
Sridhar, M. S. (2014, November 25). Types of data. Retrieved from Slideshare: https://www.slideshare.net/mssridhar/types-
of-data-42010881
Types of Data. (n.d.). Retrieved from Albany: https://www.albany.edu/~msz03/sta552/pennstate/types_of_data.pdf
VelactionVideos. (2013, April 24). Data Collection: Understanding the Types of Data. Retrieved from YouTube:
https://www.youtube.com/watch?v=Coe0N2xb8kk
What is Data. (2018). Retrieved from University of Minnesota: https://www.lib.umn.edu/datamanagement/whatdata

57. CHAPTER 1: DATA AROUND US
References:
https://examples.yourdictionary.com/independent-and-dependent-variable-examples.html
https://blog.prepscholar.com/independent-and-dependent-variables
https://studiousguy.com/sources-of-data-collection/
https://www.library.rochester.edu/Primary-secondary%20sources
https://www.diffen.com/difference/Data_vs_Information
https://keydifferences.com/difference-between-data-and-information.html
https://www.google.com.ph/search?q=examples+of+data+vs+information&hl=en-
PH&authuser=0&rlz=1C1CHBD_enPH822PH822&tbm=isch&source=iu&ictx=1&fir=DGwfETsf jWmM%253A%252C30bHKLwIqu4PiM%252C_&usg=AI
4_-kQTmAwmCPiH9ZT7EqTgASkoN98paw&sa=X&ved=2ahUKEwjnhqX_2-LeAhUMMd4KHZAADxEQ9QEwDnoECAQQBg#imgrc=DGwfETsf jWmM:
https://www.computerhistory.org/timeline/memory-storage/

58. CHAPTER 1: DATA AROUND US
THANK YOU!