10 Difference Between Data and Information.
Difference between Data and Information: These terms, with the rise of computing and the spread and integration of the study of computers in institutions of learning worldwide, have gained relevance and widespread popularity. The terms are quite interrelating and perhaps have interchangeable usages in some cases.
However, there are several cogent aspects that differentiate the one from the other. Technically, data does not become information unless it has undergone a series of processes. Data comprises uncategorized and unorganized entities that possess little or no meaning.
10 Notable Differences between Data and Information
1. Form: Basically, data is understood as a set of entities in their raw form. The form is usually of numbers, letters, or sets of characters. It can also include symbols, pictures, or audio data. Data is understood to be scattered and not aligned with some intelligible context. However, information is usually in the form of inferences, conclusions, and ideas based on processed data.
2. Input/Output: This is perhaps the simplest way to understand the difference between both terms. Data in essence is something given as input for the purpose of processing. Information is what is received as the output after processing has taken place.
3. Source: The basis for all sources of data is basically observations and records of things presented as statistics, tables, or collections of figures. However, the sole source of all information is data.
4. Utility: It is true that both data and information are both useful in their own respects. Without data in fact, there would be no information.
However, from the perspective of earnest decision making, one must realize that information is far more necessary and significant.
5. Analysis: In the raw form in which data is presented, it is never analyzed. It is recorded and presented in whatever crude format it is and given as input. The moment any form of data undergoes a process of analysis, it automatically becomes information.
6. Reliability: To speak of reliability is to speak of informed conclusions and that is essential to speak of information. A marked difference between data and information is in the presence or absence of a proper context that sets them apart.
Entities become intelligible when they are contextualized and by doing so, they become information, and conclusions based on them are more reliable.
7. Dependency: As earlier stated, without data, there can be no information. This obviously implies that all information is data-dependent. Data, in their standalone forms, are independent, both of contexts and of frames of references.
8. Representation: An understanding of the ways in which data and information may be represented is necessary to differentiate them. Commonly, data may be in structured forms, data trees, graphs, tables, etc. while information can be understood ads the ideas and thoughts that are based on the processed data.
9. Decision Making: This supremely important process is at the heart of all progressive endeavors and presents a solid lens through which data and information may be viewed. Decisions are made based only on information gotten from processed data which are arraigned in intelligible contexts. They are never made upon raw data.
10. Significance: Information proves to be far more significant as it contributes more to decision making, rationalization, and can be applied in a plethora of ways towards furthering progressive endeavors.
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