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The words “data” and “information” are often used interchangeably, but actually, there is a big difference between data and information.
Understanding that difference can be helpful, especially if you are looking to work in a field that processes a lot of data, such as Business Intelligence or Data Analysis. It can also be helpful if you are a writer, editor, teacher, or in a profession where information is critical.
Let us take a look at the difference between data and information and when you might use one word over the other.
The Difference Between Data and Information: An Overview
In a nutshell, information consists of data that has been organized and processed. However, we can also say that data is a type of information. The reverse, however, is not true: Information is not a type of data.
“There is a subtle difference between data and information. Data are the facts or details from which information is derived. Individual pieces of data are rarely useful alone. For data to become information, data needs to be put into context.”
(Note: Diffen uses “data” as a plural noun, which it was initially. Technically, the singular of data is datum. However, no-one really uses datum these days, unless they are grammar sticklers. We shall use “data” as a singular noun in this article, as is the common usage.)
The website Difference Between says the following about data vs. information:
“Data and information are interrelated. Data usually refers to raw data or unprocessed data. It is the basic form of data, data that hasn’t been analyzed or processed in any manner.
Once the data is analyzed, it is considered as information. Information is ‘knowledge communicated or received concerning a particular fact or circumstance.’ Information is a sequence of symbols that can be interpreted as a message. It provides knowledge or insight about a certain matter.”
Individual bits of data are thus used to create information, which is what you get when you read a news article, watch a newscast, or read an article such as this one.
To further understand the distinction between data and information, we can look at the definitions of these words individually.
What Exactly is Data?
The term “data” is often associated with computers and technology. We use the term “database” to describe a type of software that organizes and stores individual data items.
The term “data” is so associated with technology that the television show Star Trek: The Next Generation featured an android named Data as one of the key members of the Enterprise crew.
The association of the name “Data” with an artificial intelligence would imply that such an android would be filled with lots of, well, information, that normal people would not.
(There’s that word information again!)
By the way, you may know that “Data” from Star Trek pronounces his name with the ei diphthong, as in Day-ta. However, you can also pronounce data with the short vowel a, as in cat.
Despite its association with technology, data (no matter which way you pronounce it) does not need computers or databases to exist. Data existed before computers and will continue to exist if computers disappear off the face of the planet.
This is because data is simply a raw piece of information such as a simple fact, name, number, or address.
Examples of data include:
- Swiss cheese
- Robert Smith
- 98 degrees
“Swiss cheese” is a type of cheese, 2 is a number, Robert Smith is a name, 98 degrees is a temperature, and Alabama is a state. Separated out, these bits of data do not mean very much.
Data has to be put into context in order to become information.
What is Information?
Information is when you take those bits of data, such as facts, names, addresses, or observations of events that have happened and organize them in such a way that the data can be understood in context.
Let’s look again at those bits of data we used as examples in the last section:
- Swiss cheese
- Robert Smith
- 98 degrees
To make this data into “information,” we need to put it into context.
In this case, we might say:
With the temperature hitting a high of 98 degrees in the heart of Alabama, Robert Smith was able to make a grilled cheese sandwich with Swiss cheese and 2 slices of bread on the hood of his car.
We did, of course, include some more data in this snippet of information – where in Alabama (in this case, the “heart” of the state, which is still a bit vague), what the Swiss cheese was for (a grilled cheese sandwich), what “98 degrees” referred to, and where the action took place (the hood of Richard Smith’s car).
More About the Difference Between Data and Information
Because information can be spun and twisted easily based on what particular bits of data are used, a general consensus is that “data” tend to be more objective and “information” more subjective.
For example, if we take our last example, we can spin it one way:
With the temperature hitting a high of 98 degrees in the heart of Alabama, Robert Smith was able to make a grilled cheese sandwich with Swiss cheese and 2 slices of bread on the hood of his car. This is a clear sign that global warming is out of control.
With the temperature hitting a high of 98 degrees in the heart of Alabama, Robert Smith was able to make a grilled cheese sandwich with Swiss cheese and 2 slices of bread on the hood of his car. However, don’t take this as a sign of global warming, as this high temperature is normal for this part of the state.
Therefore, we can see that the same data can be used to push a different narrative. Although we should note that the second example references some additional data (that the high temperature is not that out of range of normal) to make its point, it doesn’t cite that data, so is it even true? (We will get into whether data can be trusted below.)
Journalists, writers, and editors also choose the angle of a story. One angle of the grilled cheese on the car story might be global warming. Another angle could be that the subject of the story, Robert Smith, is homeless and lives out of his car, and so he has resorted to using his car hood as a makeshift stovetop.
The Integrity of Data
As we have seen, data can be used in various ways to promote certain angles and narratives. There is also an issue of whether the data being referenced is actually good data.
Sometimes, a research study that has a flawed methodology may still be cited widely in newspapers and television networks even though the conclusions from the data might be quite wrong.
There is a reason why it seems we get new and contradictory dietary advice every few years. Dietary fats used to be bad, and now we know that fats can be healthy. Part of this is due to the limitations of research studies when dealing with a large and diverse population.
Another possible limitation of research studies is the technology. How much can we really learn about how the human body works, for example, when our measuring tools are still inadequate compared to the complex nature of human physiology?
Therefore, taking research studies that cite certain “data” should be done with a grain of salt.
For example, a controversial topic these days is whether children should be put on hormone blockers and sex hormones if they identify as transgender. You might come across a study that says that these hormones don’t have any negative effects, but then look more closely and see that the study only reviewed a small number of people who were on hormones in their 20s.
There would be a big difference between how a 20-year-old reacts to something as opposed to a 50 or 60-year-old.
We won’t know until 50 years from now the real impact of putting children and teens on hormone blockers and cross-sex hormones, because it is only recently that this practice has become widespread. At that point, 50 years into the future, we might have a large enough sample population to look at the long-term impact on health and wellness.
Understanding the Difference Between Data and Information
With so much data and “information” being thrown around on the Internet, taking some time to review it critically and consider whether the underlying data is good enough. Is there a big enough sample? Was the data looked at over a long enough period of time? Etc.
Now that you understand the difference between data and information and how both can be leveraged to promote various viewpoints, you can read things with a more critical eye.