Posted by Supriya Khattar at May 2, 2021


Many of the actions you make during the day become data for organisations to use for there own profit and learning.Using an automated teller machine, filling out a form for a driver’s licence, orderings book on the internet, booking a flight on an airline – all become digitised data to be sorted, managed,and used by others. In each of these cases, someone these some time has decided how the data from these users will be received, stored, processed,and made available to others.

Data and Organizations

for financial and/or legal reasons, organisations collect and store vast amounts of data about employees, customers, finances, vendors, inventory, competitors, and markets, to name only a few. The amount of data needed is important because people generally make better decisions if they have more data available to them.

For example, a car dealership, bank, or credit union will make better decisions about who to give car loans by looking at a person’s credit report information that if they simply based their decision on the word of the customer.Looking at your credit report, a bank representative would see a listing of your payment history on loans and credit card, including your mortgage. She would also see information about outstanding loans, debt repayment and credit limits. The report may also contain information about jobs you have held and public record information(birth date and address).

Likewise, a factory will improve its ability to manufacture products by tracking and managing data about inventory (name, identification number, location, and quantity), production schedule, quality control measures, and much more. You can begin to see why collecting data is important. However, the true value of data cannot be realised until it is appropriately organised, stored, analysed, and eventually used for a specific purpose.

Extracting Meaning from Data

Raw data is not very useful.Suppose a human resources manager of a local hospital sends out a survey consisting of 25 multiple-choice questions to assess the level of employee satisfaction of its 150 nurses. Let’s assume for a moment that 114 surveys are completed and returned to the manager. This is the raw data and basically has no meaning.

As a next step, the responses of each nurse to each question on the survey are entered and stored in a computer. The data is still raw and meaningless. It becomes more organised if it is entered into a computer with a plan and purpose in mind. If the manager is smart, he will assign each a nurse an ID number and enter all of his or her responses, not at random, but in the order in which they appear in the survey.

Ultimately, the data cannot be understood until it is analysed. This can be accomplished by calculating the average score for each nurse, the average score for all the nurses at the hospital, the average score for the nurses a story. Hopefully, the story will increase in a way that enables the manager to improved the level of satisfaction of the group of employees.


A character is the most basic element of data that can be observed and manipulated. Behind it are the invisible data element we call bits and bytes, referring to physical storage elements used by the computer hardware. A character is a single symbol such as a digit, letter, or other special character (e.g.,$,#,and?).


A field contains an item of data; that is, a character, or group of character that are related. For instance, a gruping of related text character such as “john smith” makes up a name in the name field. Let’s look at another example. Suppose a political action group avocation gun control in Pennsylvania is compiling the names and addresses of potential supporters for their new mailing list. For each person, they must identify the name, address, city, state, zip code and telephone number. A field would be established for each type of information in the list. The name field would contain all of the letters of the first and last name.


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