The Difference Between Data And Information
By: Terry Mansfield
Tags: Information Technology, Data Science, Information, Data Visualization, Data

The Difference Between Data And Information

It’s important for everyone to know the difference between information and data.

Photo by Stephen Dawson on Unsplash

Data can be anything like the name of a person or a place or a number, etc. Data are most useful when they are interpreted and processed to determine the true meaning, at which point data becomes what is called information. Thus, information is data processed in a way that makes it meaningful to the person who receives it via any means of communication.

While data alone may not be very informative or useful, it is, however, the basis for all reporting and analysis. The importance of data cannot be understated as it provides the basis for reporting the information required in business and other operations.

Data are the raw facts and statistics that are accurate and timely, and which are specific and organized for a particular purpose. Thus, data are crucial in supporting all types of decision-making after being transformed into useful information.

Qualitative vs Quantitative Data can be qualitative or quantitative. Qualitative data is descriptive information (it describes something) Quantitative data is numerical information (numbers) — Math is Fun

Information is data presented within a context that provides meaning and relevance, and which can lead to a decrease in uncertainty and an increase in understanding. Another way of putting it is that information is data that has been interpreted and then presented in a more meaningful and useful context.

The definition of information is news or knowledge received or given. An example of information is what’s given to someone who asks for background about something. — YourDictionary

For example, raw climate data are analyzed and processed, resulting in information interpreted for various purposes, such as is the case with climate data turned into useful, actionable information. With such information in hand, farmers can then determine which crops to grow.

Another example is raw data utilized by military commanders. After such data are processed and analyzed, a commander can then use the output as information to gain situational awareness of what is happening across the battlefield and thus make informed decisions accordingly. Correct information derived from accurate data input is critical in not only making decisions but in making the right choices; a wrong decision made in a military context can cost lives!

The bottom line is that the value of data is only as good as the quality and validity of the data used in the first place. The old maxim of ‘garbage in, garbage out’ very much applies. Good, relevant data will become valuable information that is then acted upon to make smart decisions to affect various outcomes.

However, as a cautionary note, it’s important to remember that data also can be manipulated and then interpreted in specific ways to present information that is false or misleading. As an example, in today’s divisive political environment, unscrupulous partisans of all persuasions often manipulate data to get an information outcome that favors their particular point of view or perspective at the expense of truth. Companies often do the same thing in their advertising campaigns.

Thus, consumers of data and any associated information must always be vigilant about carefully examining whatever is put before them, to make sure it is valid and worthy of believing.

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Thanks for reading.

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