What is Data? What are data types? Tools for data collection & data management Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively. ... Managing digital data in an organization involves a broad range of tasks, policies, procedures, and practices.

1. Data
Management

2. Please silent your mobile phone
During the training session

3. Data
What is data. Common type of data
Data Type
Qualitative, Quantitative (Discrete & Continuous with Example)
Data Collection
Types & Tools of data collection
Data Management
What & why Data Management, Naming convention,
Data Interpretation, Organized filing system, Advantages
Interesting Fact
Q & A

4. What is Data ?
Some Common Type of Data:
• Number (integer or floating-point)
• Boolean (true or false)
• Text (string)
• Picture
• Sound
• Video
Data is any set of characters that is gathered and translated for
some purpose, usually analysis. If data is not put into context, it
doesn't do anything to a human or computer.
Data is a collection of facts, such as numbers, words,
measurements, observations or just descriptions of things.

5. DATA TYPE
Qualitative (Categorically):
Data deals with characteristics and descriptors that
can't be easily measured, but can be observed
subjectively—such as smells, tastes, textures,
attractiveness and color.
Quantitative (Numerical):
Data deals with numbers and things you can
measure objectively: dimensions such as height,
width, and length. Temperature and humidity.
Prices. Area and volume
Discrete Continuous

6. OVERVIEW:
• Deals with descriptions.
• Data can be observed but
measured.
• Colors, textures, smells, tastes,
appearance, beauty etc.
• Qualitative  Quality
OVERVIEW:
• Deals with Numbers.
• Data which can be measured.
• Length, height, area, weight,
temperature, speed, time, ages,
numbers etc.
• Quantitative  Quantity
Qualitative Data Quantitative Data

7. Example – Qualitative
Example – Quantitative

8. Type of Quantitative Data
Discrete (Counted):
Data involves integers. For instance, the
number of children (or adults, or pets) in
your family is discrete data, because you are
counting whole, indivisible entities: you can't
have 2.5 kids, or 1.3 pets.
Continuous (Measured):
Data, on the other hand, could be divided and
reduced to finer and finer levels. For example,
you can measure the height of your kids at
progressively more precise scales Meter,
Centimeter, Millimeter etc.
Example of Discrete & Continues Data
Tally the number of
individual Candy in a
box, that number is a
piece of discrete data.
Use a scale to measure the
weight of each Candy, or
the weight of the entire
box, that's continuous data.

9. What is Data Collection?
Data collection is a methodical process of gathering and
analyzing specific information to proffer solutions to
relevant questions and evaluate the results. Types of Data Collection
Quantitative Method Qualitative Method
Primary data collection
Secondary Data Collection
It is referred to as the gathering of
second-hand data collected by an
individual who is not the original
user. It is the process of collecting
data that is already existing, be it
already published books, journals
and/or online portals. In terms of
ease, it is much less expensive and
easier to collect.
Primary data collection by definition is
the gathering of raw data collected at the
source. It is a process of collecting the
original data collected by a researcher
for a specific research purpose

10. Data Collection Tools
Observation
Data Collection
Tools
Interviews
Documents & Records
Questionnaires & Surveys

12. What is Data Management ?
Actions that contribute to effective storage, preservation
and reuse of data and documentation throughout the
research lifecycle.
Why Data Management ?
Increase Visibility &
Impact
Saves Time
Easy access of files
Increase Search
Efficiency
Why Data
Management

13. File Naming Conventions
•Include a
version number.
S.No.
File
Name
Loc.
&
Equip
Date
Version
Number
•Include serial number
in any projects file
name.
•Include project name
or number
•File names should
be short but
descriptive (<25
characters)
•Use Name or
Initials of
location or
equipment.
•Use date
format ISO
8601:
YYYYMMDD
FileName_Location_YYYYMMDD_Version
 DataMangement_KIL_20200410_1
 DataMangement_KIL_20200416_2
 Agenda_Indore_20200404_3
 Maintenance_Compressor_20191103_1

14. Architecture

15. 15
Develop & maintain
organized Records
filing system

16. 16
OBJECTIVE
To develop & maintain organized filing system in industry.
The basic objective of an organized filing system is to be able to find the record you
need quickly and economically, regardless of its location, position, format. The goal of
an organized filing system is to provide quick access to information.

17. 17
CODING / LABEL OF FILES
To make organize filing / document management system, coding or tagging has to be done on all the files.
Files can be labelled in different ways.
1. Differentiate colour of files with respect to departments.
For an example: Account – Red
HR – Blue
Sales & Purchase – Green
2. Make different codes (including year, department, sub category
and file no.) and stick on to file. Sub category is different vertical in same
department.
Sales
2018 - 19
10
01

18. Documents & Data Management SYSTEM
18
RECORD KEEPING DASHBOARD & FILE LOCATION PHYSICAL LOCATION

19. 19
ADVANTAGES AND SAVINGS FROM DOCUMENT
MANAGEMENT SYSTEM
There are many benefits of document & data management system. Here are some of them:
1. Employee can find files faster, they can accomplish more work than if they do not have to
spend time trying to locate a file.
2. Organize filing save time and space as well.
3. Indirect monetary saving.

20. Interesting Fact 2005  130 Exabyte Data
2010  1,200 Exabyte Data
2015  7,900 Exabyte Data
2020  49,000 Exabyte Data

22. THANK YOU