Data vs. Information: What’s the Difference?

5 min read
About the Author
Byron Galbraith
Byron Galbraith

As Bloomfire's Chief Scientist, Byron research is at the forefront of making artificial intelligence tools accessible to augment the performance of knowledge workers and driving productivity. Byron leads research and development around productizing AI with focus around natural language processing, natural language understanding, information retrieval, dialogue systems, machine comprehension, and program synthesis.

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    The terms “data” and “information” are sometimes used interchangeably, but they aren’t the same. Data is defined as individual facts, while information is the organization and interpretation of those facts. If data are the bricks, then information is the house they form when laid out in an organized manner.

    Ultimately, you can use the two components together to identify and solve problems. Below, we’ll take a deeper dive into data vs information and how these elements can work together in business decision-making. We’ll also take a look at how a knowledge management platform can help you organize information and establish a data-driven culture.

    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.
    Side-by-side comparison of what data is versus information

    Examples of Data vs Information

    To further explore the differences between data and information, let’s look at a few examples:

    Data Examples

    • The number of visitors to a website in one month
    • Inventory levels in a warehouse on a specific date
    • Individual satisfaction scores on a customer service survey
    • The price of a competitors’ product

    Information Examples

    • Understanding that changes to a website have led to an increase or decrease in monthly site visitors
    • Identifying supply chain issues based on trends in warehouse inventory levels over time
    • Finding areas for improvement with customer service based on a collection of survey responses
    • Determining if a competitor is charging more or less for a similar product

    As you can see, the data examples are quantitative facts that lack context on their own. But when businesses look at larger data sets and changes over time (as in the information examples), they start to uncover trends that can help them make informed decisions.

    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.

    How a Knowledge Management Platform Maximizes the Value of Data and Information

    Unfortunately, many organizations face roadblocks to creating a data-driven culture. While 26% of enterprise leaders say that all strategic decisions in their business are data-driven, another 30% say that only ‘some’ or ‘few’ are, according to an annual survey from S&P Global.

    Additionally, a study from Dimensional Research found that 82% of companies are making decisions based on outdated information.

    Decision-makers often miss opportunities to leverage data–or end up using inaccurate or outdated information–when their organization lacks a central source of truth. Different teams may collect and maintain disparate sets of data and information, leading to misalignment, inconsistencies, and lack of confidence in the information that is available to them.

    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 platform), 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.

    About the Author
    Byron Galbraith
    Byron Galbraith

    As Bloomfire's Chief Scientist, Byron research is at the forefront of making artificial intelligence tools accessible to augment the performance of knowledge workers and driving productivity. Byron leads research and development around productizing AI with focus around natural language processing, natural language understanding, information retrieval, dialogue systems, machine comprehension, and program synthesis.

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