The (Many) Differences Between Data and Information

The terms “data” and “information” are sometimes thought to be synonyms and might be used interchangeably because they both bestow some kind of knowledge upon the person on the receiving end. This is incorrect in that, while interrelated and similar in meaning, each word means actually something very specific and quite different. Not only do they have real world differences, they also play different but similar roles in the world of computing, which you can learn more about in this course about the Zen of Data. We will discuss how these two terms differ conceptually in both the everyday world as well as the world of technology.

Data Vs. Information

While this may sound like the most boring fight ever, possibly involving pocket protectors as weapons, these two concepts are basically two sides of the same coin and, in a way, two integral parts of the learning process. Here we will break down what each term means and how they relate to one another.

Data 

Data, which is the plural of the word “datum”, are basically just facts. These facts have not been processed or dealt with and are in their rawest form. Because of this raw and possibly unorganized form, data may sometimes appear random, overly simple, or abstract. Think of data as the individual pieces of a jigsaw puzzle. While you may not know exactly what you’re looking at (assuming you didn’t already look at the box the puzzle came in), you at least have an idea of what this one little part may be. Data alone and without context, like a solitary puzzle piece, is practically worthless.

Data can be further broken down into both qualitative or quantitative. Qualitative data can be observed but not measured, and deals with aspects that may be observed by the senses, i.e. color, texture, smell, taste, appearance, etc. Quantitative data is data that deals with numbers and can be measured. Criteria such as length, height, area, volume, weight, time, temperature, speed, cost, age, etc. are all considered quantitative in nature. Take, for example, a cup of coffee. The qualitative data is medium roast, strong aroma, nutty flavor, hot to the touch. The quantitative data would include its cost ($1.00), its volume (25 oz.), and its temperature (100 degrees).

In the world of computing, the concept of data is ubiquitous. It can be represented in many different ways, including tables, data trees, and graphs, among others. Data is the information that is input into the computer as quantities, characters, and symbols, then operations are performed on these data and stored as electrical signals then recorded on magnetic, optical, or mechanical recording media. A computer program’s component parts are just sets of data that are made up of coded software instructions that control the operations of a computer. This analytics course will help you work with data better as well as perform analytics better.

Information

Information is knowledge that has used and processed certain data and has rendered it useful. Using the analogy begun in the section above, information is the whole completed puzzle that the little data puzzle pieces helped you to put together. Without data there is no information – you can’t put the puzzle together if there are no pieces, or if some of the pieces are missing.

Another difference between information and data is that information is a snapshot of certain data at a single point. Data will always change as there is always more coming in. Also, data is always correct – it is a tidbit of truth, a thing that has happened. However, information can be wrong.

Information, like data, is a term that has applications when dealing with computers. If data are the tidbits that are put into the computer, it’s information that comes out as a result. If a company’s marketing department inputs data culled from their customers, their program is able to give them pertinent information based on the data it was given. This data-driven marketing course will show you how to integrate marketing with data extraction.

Knowledge

The concepts of data and information and how they relate to each other would be incomplete without mentioning the concept of knowledge. Data becomes information, which in turn is processed as knowledge, then finally manifested in a physical way as decisions and actions. Sometimes when data are missing and the information is incomplete, a person may make an assumption, where basically they fill in the blanks of the missing data. Each of these concepts are integral to the other two and without one, the others would cease to exist. This flow chart will help you visualize the processing of data.

Examples

Here are a few real world examples that illustrate the difference between data and information.

1. Data: Every few years, the government takes a census, gathering information from citizens such as yearly income, age, race, and location, among many other criteria.

Information: Alone, these bits of data are practically meaningless: 2376 San Carlos Ave., $47,000 a year, Caucasian. However, when processing this data into valuable information, the government is able to figure out pertinent statistics such as unemployment rates, average income for different parts of the state or city and other important things that have real world applications.

2. Data: A student is applying to college and she gives the college’s admissions office many pieces of info: name, address, grades, absences, letters of recommendation, etc.

Information: While the admissions office may be impressed by one A+ the student receive on a Biology project, it means nothing on its own. The student may have cheated on that project and have terrible grades otherwise. They would never be accepted to a school based on one piece of data. The school must assess ALL of the student’s data, including teachers’ opinions of them, how much school they missed, GPA, etc. Then the school is able to process the disparate data and make a decision based on this information.

So that’s data and information in a nutshell. Surely you can see why the two may get mixed up and are erroneously used as synonyms for each other, but hopefully you now know the difference between the two and will use them correctly. As important is data may be, it means nothing when not analyzed and processed into information and later a decision. Conversely, information means zilch when not backed up with data. Now go out into the world with this data, analyze it, and make good decisions based on this information!