Organization & Structure of a Computer System.

Metadata is simply defined as data about data. It means it is a description and context of the data. It helps to organize, find and understand data. A real-world example of metadata: 

Every time you take a photo with today’s cameras a bunch of metadata is gathered and saved with it. Such as

• File name,
• Size of the file,
• Date and time,
• Camera settings etc.

INFORMATION

By itself, data is not that useful. To be useful, it needs to be given context (The circumstances and settings that provide background information about an event, statement, or idea. It also helps to fully understand something). Returning to the example above, if I told you that “15, 23, 14, and 85″ are the numbers of students that had registered for upcoming classes that would be information. By adding the context – that the numbers represent the count of students registering for specific classes – I have converted data into information.

KNOWLEDGE

Once we have put our data into context, aggregated and analyzed it, we can use it to make decisions for our organization. We can say that this consumption of information produces knowledge. This knowledge can be used to make decisions, set policies, and even spark innovation. Knowledge goes beyond the individual pieces of information and involves insights, understanding, and the ability to apply information in a meaningful way.

Example: Knowing that high temperatures in a particular season can lead to increased demand for air conditioners, which can be valuable information for businesses.

The progression from data to knowledge involves a process of refining and organizing information to extract meaningful insights and understanding.

Key Differences between Data, Information and Knowledge

1. Data is fragmented pieces of symbols and characters strung together, information is refined data whereas knowledge is useful information. Additionally, data can lack context when looked at singularly, whereas information gives context to data and knowledge brings depth in understanding to such information.
2. It is noteworthy that data is incomprehensible independently, but the outcome of information is comprehension while the outcome of knowledge is understanding. Data is meaningless without being compiled into a sensible structure, while information improves representation and knowledge amplifies consciousness.
3. Data and Information alone are not sufficient to make any predictions while knowledge prediction is possible if one possesses the required experience.
4. You can’t use Data to make any statements, while information is data strung together, forming statements. Knowledge brings the ability to have a deduced conclusion using pieces of information together.
5. Data cannot independently be a basis for question formation; Information is a text that answers the questions a who, when, what, or where while knowledge is a text that answers the questions of why and how. The final difference we can consider is that data and information are easily transferable while transferring knowledge requires learning.

ASSESSMENT

1.     What is the fundamental difference between data and information?

2.     Provide an example of raw data. How does this data become meaningful in a specific context?

3.     Give an example of transforming data into information. What additional characteristics does information possess compared to raw data