The Difference Between Data, Information, and Knowledge
Data is physical appearance. and contain facts observation and perception the data processed is called information. and information that is understood is called knowledge.
knowledge is the basis for all action
knowledge is intrinsically linked to people
knowledge is created dynamically
knowledge is the result of a cognitive process
The Data and information also modify the knowledge
Knowledge can convert less value to more values
There are three types of knowledge.
1) Knowledge Psychology
i) Tacit Knowledge
ii) Explicit Knowledge
3) Knowledge Holder
i) Individual Knowledge
ii) Collective Knowledge
Declarative Knowledge:
Focus on believing in the relation among variables.
Tacit Knowledge:
Tacit Knowledge is now the term for the knowledge that is in people’s heads.
Explicit Knowledge:
Explicit Knowledge is the documented form of information.
Individual Knowledge:
individual knowledge in the person of awn knowledge is based upon the individual person. and the person transfers the knowledge of another person effectively.
Collective Knowledge:
Collective knowledge is the combination of multiple people and the transfer of knowledge effectively and essentially. collective knowledge is group decision knowledge.
Type of knowledge
Simplex Knowledge:
It is the focus of specific and general information. of individual mind
Complex Knowledge:
It is a collection of multiple experts. an expert on a particular domain.
Support Knowledge:
It depends upon the organizational infrastructure. and day-to-day progress of the organization's learning environment.
Tactical Knowledge:
It is based on short-term expertise or position.
Strategic Knowledge:
Related to long-term organization infrastructure learning time.in the term of vision or achieving the vision.
What is Knowledge and Expertise?
Information is understood and is called knowledge and Knowledge at higher quality is called expertise.
Type of Expertise.
1) Associational expertise:
It is based on experience. for example, TV technicians who learn from personal experience.
2) Motor Skills Expertise:
It is based on physical skill.
3) Theoretical (Deep) Expertise:
This kind of expert solves the unseen problem.
What are Deductive and Inductive reasoning?
Deductive Reasoning:
It deals with exact facts and exact conclusions.
Inductive Reasoning:
It is based upon a general conclusion.
STAGES OF KNOWLEDGE MANAGEMENT SYSTEM LIFE CYCLE
The first stage is
evaluate the existing infrastructure: In this phase analyze which information is transferred and departure to the other firms and analyze the vision resources culture to analyze the existing environment. and capture real-time data.
Knowledge Management Team: In this phase identify the key stakeholders. The team is successfully implemented.
knowledge capture from different environments: There the two types of capture knowledge tacit or explicit knowledge tacit knowledge is inside the brain. explicit knowledge is for documented form.
Design the knowledge management blueprint: It is the prototype the prototype is defined that the system analysis and the user collect the system requirement. the
Verify and validate the knowledge management system: IT is the testing process of knowledge management system verify to ensure that the system is right function validate to ensure that the system is right output.
Implement the knowledge management system: Converting the knowledge management system to actual operation by converting data into files also includes user training
Manage changes and rewards structure: If the system has the changes or the update of the knowledge management system through projection, avoidance, or aggression.
Post-system evaluation: It is based upon the Impact of people, procedures, and performances.
The
Difference Between Data, Information, and Knowledge
The terms data, information, and knowledge are often used
interchangeably. But they actually have different meanings. Data is the rawest
form of information. Information is data that has been processed in some way.
And knowledge is information that has been processed in a way that makes it
meaningful and useful.
Think of it this way: data is the seed, information is the
plant, and knowledge is the fruit. The seed is the basic raw material. But it’s
not very useful on its own. The plant is more useful because it has been
processed in some way. And the fruit is even more useful because it has been
processed in a way that makes it more valuable.
Data, information, and knowledge are all important. But they
are not the same thing.
1. Data is the lowest
level of understanding.
2. Information is
data that has been interpreted and organized.
3. Knowledge is
information that has been interpreted, organized, and used.
4. Data is
meaningless without interpretation.
5. Information is
data with interpretation.
6. Knowledge is
information with interpretation and application.
7. Data, information,
and knowledge are all interconnected.
1. Data is
the lowest level of understanding.
Data is the most basic level of understanding. It is a
collection of facts and figures that can be processed to give information. Data
can be qualitative or quantitative. Qualitative data is data that can be
described, such as "tall", "short", "red",
"green", etc. Quantitative data is data that can be measured, such as
"height", "weight", "distance", etc.
2.
Information is data that has been interpreted and organized.
Data is the building blocks that provide the foundation for
information and knowledge. Data isrekfkjewlk
lkfjweio data that has been interpreted and organized. This
interpretation and organization of data into information requires the use of
some level of human cognitive processing. In other words, information is data
that has been interpreted by a human and organized in a way that is meaningful
to that human.
The cognitive processing required to interpret and organize
data into information can be as simple as recognizing a pattern or trend. For
example, if you are looking at a graph of monthly sales data, you might use
your cognitive processing skills to interpret the data and see that there was a
significant increase in sales from January to February. This would then be
organized into the information that there was an increase in sales from January
to February.
The cognitive processing required to interpret and organize
data into information can also be more complex. For example, if you are looking
at a set of data about the number of hours of sunshine each day for a month,
you might use your cognitive processing skills to interpret the data and see
that there is a correlation between the amount of sunshine and the number of
hours people spend outside. This would then be organized into the information
that there is a correlation between the amount of sunshine and the number of
hours people spend outside.
The cognitive processing skills required to interpret and
organize data into information can vary depending on the individual and the
type of data being interpreted. Some people may be better at recognizing
patterns and trends, while others may be better at more complex data analysis.
Regardless of the individual skillset, the goal is to produce meaningful
information from data.
Once data has been interpreted and organized into
information, it can then be used to generate knowledge. Knowledge is
information that has been interpreted, organized, and then used to form a new
understanding or insights. For example, if you are looking at a set of data
about the number of hours of sunshine each day for a month, you might use your
cognitive processing skills to interpret the data and see that there is a
correlation between the amount of sunshine and the number of hours people spend
outside. You might then use this information to generate the knowledge that
people are more likely to spend time outside when there is more sunshine.
The cognitive processing skills required to generate
knowledge from information can vary depending on the individual and the type of
information being used. Some people may be better at recognizing patterns and
trends, while others may be better at more complex data analysis. Others may be
better at making connections between different pieces of information to form
new understandings. Regardless of the individual skillset, the goal is to
produce new knowledge from information.
Data, information, and knowledge are all interrelated. Data
is the foundation for information and knowledge. Information is data that has
been interpreted and organized. Knowledge is information that has been
interpreted, organized, and then used to form a new understanding or insight
3.
Knowledge is information that has been interpreted, organized, and used.
Data, information, and knowledge are all related concepts,
but they are not the same thing. Data is the raw material that can be used to
create information and knowledge. Information is data that has been organized
in a way that is meaningful to someone. Knowledge is information that has been
interpreted, organized, and used.
To really understand the difference between data,
information, and knowledge, let's look at an example. Imagine you are looking
at a list of items for sale at a store. The list is just a bunch of data. It is
meaningless until it is organized in a way that you can understand. This is
information. Once you have the information, you can use it to make decisions.
For example, you might use the information to decide to buy one of the items on
the list. This is knowledge.
Data, information, and knowledge are all important. Data is
the raw material, information is the organized data, and knowledge is the
interpreted and used data.
4. Data is
meaningless without interpretation.
Data is meaningless without interpretation. This is because
data, by itself, is just a collection of facts and figures. It is only when
these facts and figures are interpreted that they become meaningful.
For example, consider a data set that contains information
about the ages of all the students in a particular class. This data set, by
itself, is not terribly interesting or meaningful. However, if we were to
interpret this data set, we might notice that the ages are all clustered around
a particular value, which might tell us something about the students in that
class.
Similarly, if we have a data set that contains information
about the speeds of cars on a particular road, we might be able to interpret
this data to understand the flow of traffic on that road.
In short, data is meaningless without interpretation because
interpretation is what gives data its meaning.
5.
Information is data with interpretation.
Information is data with interpretation. It is data that has
been processed in such a way that it is meaningful and useful to the person who
receives it.
For example, data is a collection of facts and figures.
Information is what that data means. It is the interpretation of the data that
makes it useful.
Knowledge is information that has been interpreted and
assimilated by the person who receives it. It is information that has been
understood and integrated into the person's understanding of the world.
Data, information, and knowledge are all related, but they
are not the same thing. Data is the raw material from which information and
knowledge are created. Information is data that has been processed and given
meaning. Knowledge is information that has been interpreted and assimilated.
6.
Knowledge is information with interpretation and application.
Information is knowledge that has been interpreted and
applied. In other words, knowledge is information that has been processed and
given meaning. Most people think of knowledge as simply information, but it is
much more than that. It is information that has been organized, explained, and
put to use.
Consider a doctor who has been diagnose a patient with a
rare disease. The doctor has read about the disease, seen it in other patients,
and has a general understanding of how it works. But the doctor also knows how
to apply this information to the specific case at hand. He or she knows how to
diagnosis and treat the disease, based on the unique circumstances of the
patient. This is what separates knowledge from mere information.
To further illustrate the point, consider a person who has
just been given a recipe for a cake. The person has all the information they
need to make the cake, but they lack the knowledge of how to actually make it.
They might not know how to measure the ingredients, how to turn on the oven, or
what temperature to bake the cake at. In order to transform the information
into knowledge, they would need to learn these things.
In summary, knowledge is information that has been
interpreted and applied. It is information that has been organized, explained,
and put to use. Knowledge is power, and it is what separates the experts from
the novice.
7. Data,
information, and knowledge are all interconnected.
Data, information, and knowledge are all interconnected.
Data is the raw material from which information and knowledge are derived.
Information is data that has been organized and interpreted. Knowledge is
information that has been organized and interpreted in such a way that it can
be used to solve problems or make decisions.
The three terms are often used interchangeably, but there
are important differences between them. Data is the most basic element. It is
the raw material from which information and knowledge are derived. Information
is data that has been organized and interpreted. Knowledge is information that
has been organized and interpreted in such a way that it can be used to solve
problems or make decisions.
Data is collected through observation and measurement. It
can be quantitative, such as numbers, or qualitative, such as descriptions.
Data can be structured, such as in a database, or unstructured, such as in a
text document.
Information is data that has been organized and interpreted.
It is created when data is sorted, categorized, and given meaning. Information
can be presented in different forms, such as text, images, and numbers.
Knowledge is information that has been organized and
interpreted in such a way that it can be used to solve problems or make
decisions. It is the result of applying information to real-world situations.
Knowledge is often tacit, or unspoken, and is difficult to formalize. It is
usually more helpful to think of knowledge as a process, rather than a product.
In summary, data is the building blocks of information and
knowledge. Information is organized data that has meaning. Knowledge is
understanding gained from Processing and understanding information.
Differentiating between the three is important in order to understanding how
they are all used in different ways to obtain different results.