Structured vs. Unstructured Data: Definition & Examples

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  • 0:00 What Is Data?
  • 0:49 Structured Data
  • 2:39 Unstructured Data
  • 3:46 Data Types Used Together
  • 4:46 Lesson Summary
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Lesson Transcript
Instructor: Lucinda Stanley

Lucinda has taught business and information technology and has a PhD in Education.

In this lesson you will learn what structured and unstructured data are and how they are different. You will also see how both are used and see some examples of each type of data.

What Is Data?

Which of these cars will you buy?

Car Decision: No Data
Car: No Data

What do you mean you can't make that decision? Are you thinking to yourself you need more information? You probably do if you want to make a good decision.

So, what is it you need? You need data! This is true of business decisions as well - more data generally means less risk in decision making. The better the data, the lower the risk. Making a decision without data increases the risk that the decision will be faulty.

So, you know you need lots of data, but what does data look like? You're probably thinking of lots of numbers and maybe some charts and graphs. But data comes in many forms and is often categorized as structured and unstructured. Let's take a look at what they each represent.

Structured Data

Some business experts estimate that about twenty percent of all data used in business decisions is structured data. Structured data is easily organized and generally stored in databases. Structured data generally consists of numerical information and is objective. It simply is data that exists - there is no interpretation.

Some types of structured data can be machine generated, such as data that comes from medical devices (heart rate, blood pressure), manufacturing sensors (rotation per minute, temperature), or web server logs (number of times a page is visited). Structured data can also be human generated - data such as age, zip code, and gender.

If we think about the structured data a web server log might keep, we could find out how many customer inquiries there have been, how long it took to solve a problem, and how the customer rated his experience.

So, in our example of the choice between cars, what structured data do you want to know?

Car Decision: Structured Data
Car Decision: Structured Data

These data are easily comparable - 28 miles per gallon is better than 16 miles per gallon, and though the Saturn is newer, it only seats 2 people compared to 5 in the Jeep.

Let's look at another data set. In the following graph, we can see how fuel efficiency, in miles per gallon, has changed over the years for passenger cars, larger vehicles, and heavy-duty trucks.


This is all factual data, but the data may not tell you everything you want to know. What we can't see in this data is how increased fuel efficiency affects performance or price, what historical events or legislature caused these changes, or why it has not increased for trucks at all!

After you get the facts from the structured data, you then look to sources of unstructured data to flesh out the scenario.

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