1.1 Data, Information and Knowledge
In this article we are going to discuss three things like DATA, INFORMATION, and KNOWLEDGE and there relation between them. Basically in this article we are going to go through the definition of each according to the organisational point of view, how are they used by an organisation and there importance within and outside an organisation. We are also going to discuss the process through which organisation maintain its DATA, INFORMATION, and KNOWLEDGE. First of all we are going to define each of them and then do critical analysis on them
Definition:
According to Prof. Michael Buckland
DATA: The word "data" is commonly used to refer to records or a recording encoded for use in computer, but is more widely used to refer to statistical observations and other recordings or collections of evidence. (Prof. Michael Buckland, University of California, Berkeley, USA)
INFORMATION: The word “information” is used to refer to a number of different phenomena. These phenomena have been classified into three groupings: (1) Anything perceived as potentially signifying something (e.g. printed books); (2) The process of informing; and (3) That which is learned from some evidence or communication. All three are valid uses (in English) of the term “information”. I personally am most comfortable with no. 1, then with no. 3, but acknowledge that others have used and may use no 2. (Prof. Michael Buckland, University of California, Berkeley, USA)
KNOWLEDGE: The word “knowledge” is best used to refer to what someone knows, which is, in effect, what they believe, including belief that some of the beliefs of others should not be believed. By extension the word “knowledge” is used more loosely for (1) what social groups know collectively; and (2) what is in principle knowable because it has been recorded somehow and could be recovered even though, at any given time, no individual knows (or remembers) it. (Prof. Michael Buckland, University of California, Berkeley, USA)
According to Russell Ackoff, a systems theorist and professor of organizational change
DATA: Data is raw. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer parlance, a spreadsheet generally starts out by holding data. (Ackoff, R. L)
INFORMATION: Information is data that has been given meaning by way of relational connection. This "meaning" can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it. (Ackoff, R. L)
KNOWLEDGE: Knowledge is the appropriate collection of information, such that its intent is to be useful. Knowledge is a deterministic process. When someone "memorizes" information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, integration such as would infer further knowledge. For example, elementary school children memorize, or amass knowledge of, the "times table". They can tell you that "2 x 2 = 4" because they have amassed that knowledge (it being included in the times table). But when asked what is "1267 x 300", they cannot respond correctly because that entry is not in their times table. To correctly answer such a question requires a true cognitive and analytical ability that is only encompassed in the next level... understanding. In computer parlance, most of the applications we use (modelling, simulation, etc.) exercise some type of stored knowledge. (Ackoff, R. L)
Some definitions of data, information, and knowledge.
From a Business Point of View
The following three definitions are quoted from Godbout (January 1999).
Data constitutes one of the primary forms of information. It essentially consists of recordings of transactions or events which will be used for exchange between humans or even with machines. As such, data does not carry meaning unless one understands the context in which the data was gathered. A word, a number or a symbol can be used do describe a business result, inserted in a marriage contract or a graffiti on the wall. It is the context which gives it meaning, and this meaning makes it informative.
Information extends the concept of data in a broader context. As such it includes data but it also includes all the information a person comes in contact with as a member of a social organization in a given physical environment. Information like data, is carried through symbols. These symbols have complex structures and rules. Information therefore comes in a variety of forms such as writings, statements, statistics, diagrams or charts. Some information theorists insist on the concept of form as the differentiating factor and the essence of information.
Where does knowledge fit in this scenario? Information becomes individual knowledge when it is accepted and retained by an individual as being a proper understanding of what is true (Lehrer, 1990) and a valid interpretation of the reality. Conversely, organizational or social knowledge exists when it is accepted by a consensus of a group of people. Common knowledge does not require necessarily to be shared by all members to exist; the fact that it is accepted amongst a group of informed persons can be considered a sufficient condition. This is also true of «public domain» knowledge. The fact that it is readily available in writing or published material does not entail that everybody should be knowledgeable about it to meet the condition of being "common knowledge".
Godbout presents these definitions in an article discussing roles of computers in the field called "knowledge management." Knowledge management is of steadily growing importance in running a business or similar types of organizations.
Now we talk about the relation between data, information and knowledge, basically in this discussion we will talk about data, how it is been transferred into information and then into knowledge. What are the key issues which make these changes happen and how organisations use them?
In the good old days, in the early history of using computers to do business data processing, computers were data processing machines. There were lots of workshops and courses on data processing. "Raw data" was processed to produce reports that were then analyzed by management to make management decisions. Hourly time sheets of workers were processed to produce payroll checks and summary reports on employee costs.
Later came the idea of computers processing data to produce information. Payroll data can be put together with other cost data, sales data, and so on to produce information about which products are most profitable. The huge collection of raw data can be processed into reports that facilitate high level management decisions.
Computer Science Departments became Computer and Information Science Departments. Terms such as Information Technology (IT) and Information and Communication Technology (ICT) arose because they better described the computer field.
In more recent years, businesses and others have worked to use computers to process information so that it becomes or is closely similar to knowledge. Knowledge in a person's head is used for posing and solving problems, posing and answering questions, defining decision making situations and making decisions, posing tasks to be accomplished and accomplishing the tasks, and so on. Nowadays, computers make lots of decisions without human intervention. That is, they receive data as input and they process it in a manner that produces decisions and actions as output. When a human does this, we talk about the level of knowledge, skill, and intelligence that the person has.
The "Data to Wisdom" Curve by Bob Thomson,
on the Canadian Web, igc:p.news, May 26, 1994
The graph above reflects the learning journey whereby we progressively transform the raw, unfiltered facts and symbols into information, knowledge, and eventually into intelligence and wisdom.
Now if we look at the organisational level how we use data, information and knowledge, well talking about organisation, let’s take a real life example of Curry’s super store where I am working as well. All the products which are been displayed in the shop have a unique product code which helps the system keep track of everything and to keep everything in proper context. The system which is been used in the store is called “ESCLIPS”, so whenever a new product is been enter into the system all the details regarding that product is been treated as data for example “123456 HOTPOINT DG3342 1400 6 KG” in this what is 123456, what is HOTPOINT, what is DG3342, what is 1400, what is 6KG these are just random data or raw data which means nothing to anyone, same as this is nothing to the system, so to convert that data to information we have to put that data into proper context or we can say giving a proper meaning to that data, so to accomplish that state which is called information we have to arrange this data under proper heading or context, for example let’s take a word “rosemary” for me it’s a name of a herb and for Prof. Mark its name of his girl friend, so in order to make it more meaning full we have to put “rosemary” in a proper context. Same case with the “123456 HOTPOINT DG3342 1400 6KG” we have to put it in a proper context to make it more use full. So the system basically put this data into proper context so that it can be more use full and used as information about that specific product. So now if u look at “123456 HOTPOINT DG3342 1400 6KG” under proper context
| Product code | Product Name | Model no. | weight load | Spin speed |
| 123456 | Hotpoint | DG3342 | 6 KG | 1400 |
Everything has proper meaning under proper context and this is used as information by the system and any member of staff or organisation. So by putting all the data under proper context it’s been changed to a state which is called information.
Now we talk about how information is been changed to knowledge. Knowledge is last but least state of data, in this state or when we talk about knowledge
“Knowledge is internalized or understood information that can be used to make decisions” (Prof. Carol Tenopir, University of Tennessee, USA)
Let’s continue the example of curry’s super store, after putting the data into proper context to make it information now we know that “123456 HOTPOINT DG3342 1400 6KG” is information about a specific product, now any member of the store (organisation) can use it as knowledge to make a better decision at any point. So now this “123456 HOTPOINT DG3342 1400 6KG” information shows that it is a product which is in a category of house hold product and it is a type of a washing machine, so this information/knowledge will help the staff member or member of organisation to help the customer in order to find a proper product according to the needs of the customer. This better decision is been done by the help knowledge of the staff member, at this point I will quote and knowledge definition by Prof. Irene Wormell, Swedish School of Library and Information Science in Borås, Sweden
Knowledge is enriched information by a person's or a system's own experience. It is cognitive based. Knowledge is not transferable, but through information we can communicate about it (Prof. Irene Wormell, Swedish School of Library and Information Science in Borås, Sweden)
