Data vs Information: What’s the Difference?

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Jon Hill
4 mins
data visualization above tablet represents data vs information

The terms “data” and “information” are often used interchangeably, but they actually aren’t the same. There are subtle differences between these components and their purpose. Data is defined as individual facts, while information is the organization and interpretation of those facts.  

Ultimately, you can use the two components together to identify and solve problems. Below, take a deeper dive into data vs information and how these elements can be applied in a business environment.

What Is Data?

Data is defined as a collection of individual facts or statistics. (While “datum” is technically the singular form of “data,” it’s not commonly used in everyday language.) Data can come in the form of text, observations, figures, images, numbers, graphs, or symbols. For example, data might include individual prices, weights, addresses, ages, names, temperatures, dates, or distances.

Data is a raw form of knowledge and, on its own, doesn’t carry any significance or purpose. In other words, you have to interpret data for it to have meaning. Data can be simple—and may even seem useless until it is analyzed, organized, and interpreted.

There are two main types of data:

  • Quantitative data is provided in numerical form, like the weight, volume, or cost of an item.
  • Qualitative data is descriptive, but non-numerical, like the name, sex, or eye color of a person.

What Is Information?

Information is defined as knowledge gained through study, communication, research, or instruction. Essentially, information is the result of analyzing and interpreting pieces of data. Whereas data is the individual figures, numbers, or graphs, information is the perception of those pieces of knowledge.

For example, a set of data could include temperature readings in a location over several years. Without any additional context, those temperatures have no meaning. However, when you analyze and organize that information, you could determine seasonal temperature patterns or even broader climate trends. Only when the data is organized and compiled in a useful way can it provide information that is beneficial to others.   

The Key Differences Between Data vs Information

  • Data is a collection of facts, while information puts those facts into context.
  • While data is raw and unorganized, information is organized.
  • Data points are individual and sometimes unrelated. Information maps out that data to provide a big-picture view of how it all fits together.
  • Data, on its own, is meaningless. When it’s analyzed and interpreted, it becomes meaningful information. 
  • Data does not depend on information; however, information depends on data.
  • Data typically comes in the form of graphs, numbers, figures, or statistics. Information is typically presented through words, language, thoughts, and ideas.
  • Data isn’t sufficient for decision-making, but you can make decisions based on information.

Examples of Data vs Information

To further explore the differences between data and information, consider these examples of how to turn data into insights:

  • At a restaurant, a single customer’s bill amount is data. However, when the restaurant owners collect and interpret multiple bills over a range of time, they can produce valuable information, such as what menu items are most popular and whether the prices are sufficient to cover supplies, overhead, and wages.
  • At a restaurant, a single customer’s bill amount is data. However, when the restaurant owners collect and interpret multiple bills over a range of time, they can produce valuable information, such as what menu items are most popular and whether the prices are sufficient to cover supplies, overhead, and wages.
  • At a restaurant, a single customer’s bill amount is data. However, when the restaurant owners collect and interpret multiple bills over a range of time, they can produce valuable information, such as what menu items are most popular and whether the prices are sufficient to cover supplies, overhead, and wages.
  • At a restaurant, a single customer’s bill amount is data. However, when the restaurant owners collect and interpret multiple bills over a range of time, they can produce valuable information, such as what menu items are most popular and whether the prices are sufficient to cover supplies, overhead, and wages.
  • At a restaurant, a single customer’s bill amount is data. However, when the restaurant owners collect and interpret multiple bills over a range of time, they can produce valuable information, such as what menu items are most popular and whether the prices are sufficient to cover supplies, overhead, and wages.

How Businesses Can Leverage Data and Information 

Why does the distinction between data vs information matter for businesses? Organizations that prioritize collecting data, interpreting it, and putting that information to use can realize significant benefits. When used correctly, data (and the information that’s gleaned from it) can drive smarter and faster business decisions.

For example, a company might gather data about the performance of their ads or content. They could organize and interpret that data to produce a wealth of insights, like what types of graphics, phrases, and even products are most appealing to their customer base. They may also be able to develop a more comprehensive understanding of their target audience, which can help them make decisions about future offerings, branding, and communication preferences. The right data can lead to nearly limitless information and insights—all invaluable for decision-making.

However, there can be several roadblocks to creating that sort of data-driven organizational culture. For example, different teams may collect and maintain disparate sets of information. Without a central database, others in the company can’t interpret or benefit from that data. In addition, if no one consistently oversees the data, the data may not be of adequate quality for interpretation—and as a result, any information derived from that data could be misleading or inaccurate.

To create a truly effective data-driven culture, it’s critical that you maintain the information and insights gleaned from data in a centralized source that’s available organization-wide (like a knowledge management system), implement protocols to ensure data quality, and cultivate analytics skills across all departments.

Data and information are both critical elements in business decision-making. By understanding how these components work together, you can move your business toward a more data- and insights-driven culture.

June 15, 2021

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