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Business relies on meaningful data patterns to get information, in this article let’s explore the differences and similarities between data and information.
Misunderstanding the difference between “data” and “information” sets up the stage for mistakes. Like the six blind men in an Indian parable, trying to describe an elephant, you end up confusing individual facts, or data, as information or meaning.
In the six blind men’s dilemma, each confuses data (the trunk or the legs) for information (an elephant is a giant snake, or an elephant is a giant cow). Similarly, you can gather customer data and think you have the full customer information when you do not.
Data and information have specific applications. To correctly recognize and use either one, you need to understand the difference between data and information is. We’re going to explore various questions in this article, skip ahead to your interest if you please.
- What is Data vs. Information?
- Are Data and Information the Same Thing?
- How Do Data and Information Differ?
- How Do You Distinguish Information from Data?
- Final Words
What is the difference between data and information?
Data describes figures and facts. It may consist of one entry or a collection of different values. Information describes values and context together, resulting in something meaningful. It forms an organized and cohesive structure, from data, to interpret or communicate the whole.
Digging deeper, the Latin root of the word “data” means “something given,” a piece of a larger picture. Data must apply to a context or a reason to do something about it. It shows up in a raw, unprocessed, and unorganized form.
Data Example
For data examples, we can use ‘J, Smith,123 King St, London, UK, 0202656788’. The commas represent each separate fact that may or may not be related to others.
Information Example
In this example of information, Each fact relates to other facts to form a concept, known as John Smith. Creating this John Smith entity allows people to reason, calculate, and do other manipulations.
John Smith
123 King Street
London, United Kingdom
(020) 2656788
When you want something technical to achieve a business purpose, like storing or efficiently retrieving values, you use data. When you want to do something more abstract, like creating mailing address labels or preparing sales and marketing letters, you use information.
Are Data and Information the Same Thing?
From a content and format perspective, data and information may be the same thing. For example, you can point to the same values in two different columns on a spreadsheet.
However, data and information contents and formats do not have to match. In any case, you use data and information very differently.
Say you want to export all customers in your spreadsheet that has the value “London, United Kingdom” You will filter data named “London” under city and “United Kingdom” under country. Upon seeing the resulting data set presented, you start the export.
On the same spreadsheet, say you want to know if the John Smith records mean the same person. You look at the information in both rows and see, spread across the columns:
John Smith
123 King Street
London, United Kingdom
(020) 2656788
You determine both John Smiths, living in London, United Kingdom, mean the same customer entity from the information provided. Are data and information interchangeable? In this case of a duplicate, both John Smith records that match, Yes.
How Do Data and Information Differ?
Data and information may have the same values but differ in their creation and business usage. Information contains context, whereas data, literally, just includes entries. Information can contain data with different contents and formats and be the same thing.
From a data perspective, “United Kingdom,” “UNITED KINGDOM,” and “U.K.” represent entirely different facts. The number of characters and formatting varies. Therefore, John Smith, who lives in the U.K., is not the same customer as John Smith, who lives in the United Kingdom.
From an information viewpoint, the “United Kingdom,” “UNITED KINGDOM,” and “U.K.” represent the same thing, a shared data pattern about a geographical reason. You know this because someone with some understanding of geography can point to the “United Kingdom” or the “U.K.” on a European map. Other people will also point to an identical geographical area.
The correct data and accompanying context make the United Kingdom and the U.K. contain meaning about a shared concept of that region, like culture, sports, and government. You can take John Smith, who lives in the U.K., with John Smith that lives in the United Kingdom, and consider creating the same entity. You can compare this John Smith with other people in the United Kingdom and gain insights, adding additional data points, like what music people in Great Britain (aka the U.K) prefer.
Information has more power than data. Without information, people would take a long time communicating, interpreting, and combining the same thing. You would say John Smith lives where you use grams to weigh stuff, find Dublin, Edinburgh, and London, and eat fish and chips.
Instead, these details and more can be related and connected to one mental image or pattern, the United Kingdom, or the U.K. As a result, people and computers can better process and transform the data. Information allows you to export all your customers from the same country, whether the data value reads “United Kingdom,” “U.K.” “Great Britain,” or “UNITED KINGDOM.”
How to Distinguish Information from Data?
So how do you know whether the value “United Kingdom” is data or information given the same contents and formatting? You see the difference by the questions you want to know.
You do data when you want to know what country to enter a country for the first ten records of a database. The answer consists of a value like the “United Kingdom.”
You do information when you ask about the customer entity John Smith that lives on King Street in the U.K. For example, you want to know where he likes to shop or what market literature he has received.
Information contains data patterns, like a picture. When businesses want to understand their customers, they want to have a picture of each. When visualizing the person, John Smith, the marketer, or salesperson, means the person with all these facts (123 King Street, London, United Kingdom, (020) 2656788) and more data.
These patterns used to create customer information can be identified and put together by data governance (shared processes around), business objectives, or fuzzy matching, computer algorithms that identify like entities. Getting customer information from data matching, data cleansing, and master data management technologies gets you customer information more quickly than manually stringing all this data together as information.
To read more about data management, make sure you check out our comprehensive MDM guide here!
Final Words:
Understanding the difference between data and information means knowing which one to choose and when. When you want to know what values a system contains or make the computer do a technical process, you want data. When you want to deal with entities, such as customers, products, or locations, you want to do information.
You want to get the right information from data patterns to gain accurate insight. The blind men, in the parable above, got aspects of what makes an elephant. But the men needed to combine all their observations to understand an elephant.
Likewise, data managers can get stuck interpreting individual customer data points missing information about the customer. Then customers get duplicate mailings or contacted in error, costing money and time.
Businesses need to create information from meaningful data. One aspect of this activity, Master Data Management, can help you better work with the differences between data and information.
