DATA, INFORMATION AND KNOWLEDGE

DATA, INFORMATION AND KNOWLEDGE 

Data is raw material with which we start and information is the finished product.

For example, look at the following links:

1234           5000.00

2345           7000.00

3456           4500.00

2571           8000.00

You would agree that the above lines contain data. But in the present form, the above data is useless. Let me now put the data in the proper context as follows:

Account Number	Money withdrawn on 25/02/2014
1234	5000.00
2345	7000.00
3456	4500.00
2571	8000.00

 

The data is now usable and we can process it to extract information such as the amount withdrawn from account number 1234 is 5000.00. We can consolidate the data and extract the information that Rs. 24500.00 were withdrawn on 25/2/04.

Information has been defined as :

Data that have been put into a meaningful and useful context and communicated to a recipient who uses it to make decisions it reduces uncertainty, reveals additional alternatives or helps eliminate irrelevant or poor ones.

Returning back to our example, the bank manager may decide the amount of required cash based on the information of total money withdrawn.

The information makes a person more knowledgeable. Knowledge is an awareness and understanding of a set of information that help decision-making. Knowledge makes a person wise. The sequence is the following-data is processed to get information; information makes a person knowledgeable, knowledge adds to the wisdom.

The information should have certain characteristics to be valuable to its recipient. These characteristics vary from being accurate to secure. If information is not accurate, the decision maker may not rely on the information. The situation becomes worse if the recipient of the information is not aware of its inaccuracy. The decision maker may use inaccurate information assuming it to be accurate. The following is a comprehensive list of desired characteristics: 

1) Accurate: The information should be accurate and error free. The information may be inaccurate due to incorrect data that has been used to generate information. The data may be inaccurate due to human error. This is commonly referred to as garbage-in-garbage-out (GIGO).

2) Complete: The information must be complete. The information should not have been filtered that presents a biased picture to the recipient. Let us say, salespersons of organizations are reporting sales information to the sales manager. They make those sales for month of July are exceptionally low. They delete this information from their report whereas the sales manager might be interested in July sales just as much as in other month’s sales. He might even be aware of the seasons for the dip and might be planning to boost sales in July. The incomplete information may be useless for him.

3) Economical: We all understand that information has an associated cost and it is expected to be beneficial for the recipient. The benefit must be much greater than the cost.

4) Flexibility: Let us understand flexibility through an example. In a bank, the bank manager would like to know the total amount withdraw and deposited through transactions distributed and recovered through bank. A client would like to check the total money he withdraws from his account and his present balance. The information that the bank possesses should be flexible enough to present different views of data to different people.

5) Reliable and verifiable: Information is said to be reliable if one can depend on it. The sum of data and information both should be reliable. In case, there is any doubt or the user wants to be absolutely sure, he might like to verify.

6) Relevant: This Characteristic is self-explanatory.

7) Simple: The information must be presented in proper format to make it simple for user. Too much information may result in information overload. The user may not be able to extract important information.

8) Timely: The information may lose its value if it is not received in a timely manner. Imagine reading yesterday’s newspaper today.

9) Accessible and secure: The information should be easily accessible to authorized persons. At the same time, the information should be secure from unauthorized users.

To summarize, information is the result or product of processing data as depicted below.

 

 

Data Life Cycle

We can think of data having their own life cycle namely, data generation, data manipulation, transmission of data (and communication of information) and storing/ retrieving and reproduction data.

The generation of data could take place internally and/or externally. This data has to be captured by recording of data from an event or occurrence in some form such as sales slips, personnel forms, purchase order etc.

The captured data would have to be stored either in person’s mind or in document or in ‘mechanical’ or electronic device, microfilm, and punched cards/tapes or in device of some suitable form before they may be operated upon or authorized.

Stored data would have to be retrieved by searching out and gaining access to specific data elements from the medium where it is stored.

Retrieved data may be converted or reproduced to different form storage or presentation format by way of documents reports etc.

Data are also constantly being transported to the user in processed form. It is transferred to storage from the source, then processed and passed on the user, who again returns it to storage after working on it, which becomes available for further retrieval.

The randomly accumulated data has to sorted and classified to reveal appropriate information. For example, sales data can be classified product-wise, territory-wise, salesperson-wise etc. Such a classification will give the sales data more meaning.

Sometimes aggregation or synthesis of many pieces of data to structure a meaningful whole or complete report is often required.

Processing of data might entail quite a bit of manipulation and calculations involving addition, subtraction, multiplication, division etc. based on certain formulae. Computations might have to be performed for deriving employee’s pay, customer’s bill, financial ratios etc. Management science/operational research models might be used for determining optional product mix, aggregate planning, and economic order quantity determination.

Data stored must be utilized on some occasion by someone at some point of time; otherwise there is no point in putting it in the inventory. When data is finally put in a usable form it can be retrieved and turned into information at appropriate time for decision-making.

Some types of a continuous verification and evaluation of data ought to be taken because there is also an economic aspect of cost processing data versus the value of information. Therefore, data files should be continuously monitored to eliminate useless data.

It is important to destroy data following its evaluation or use. Destruction of data records may be on a purely routine basis following one time use or may occur in review of old records. Destruction is the terminal stage or the end of the data life cycle.