Which of the following statements below shows the contrast between data and information?

Data vs. Information - Differences in Meaning

"The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning." —Statistician Nate Silver in the book The Signal and the Noise

Data are simply facts or figures — bits of information, but not information itself. When data are processed, interpreted, organized, structured or presented so as to make them meaningful or useful, they are called information. Information provides context for data.

For example, a list of dates — data — is meaningless without the information that makes the dates relevant (dates of holiday).

"Data" and "information" are intricately tied together, whether one is recognizing them as two separate words or using them interchangeably, as is common today. Whether they are used interchangeably depends somewhat on the usage of "data" — its context and grammar.

Examples of Data and Information

  • The history of temperature readings all over the world for the past 100 years is data. If this data is organized and analyzed to find that global temperature is rising, then that is information.
  • The number of visitors to a website by country is an example of data. Finding out that traffic from the U.S. is increasing while that from Australia is decreasing is meaningful information.
  • Often data is required to back up a claim or conclusion (information) derived or deduced from it. For example, before a drug is approved by the FDA, the manufacturer must conduct clinical trials and present a lot of data to demonstrate that the drug is safe.

"Misleading" Data

Because data needs to be interpreted and analyzed, it is quite possible — indeed, very probable — that it will be interpreted incorrectly. When this leads to erroneous conclusions, it is said that the data are misleading. Often this is the result of incomplete data or a lack of context. For example, your investment in a mutual fund may be up by 5% and you may conclude that the fund managers are doing a great job. However, this could be misleading if the major stock market indices are up by 12%. In this case, the fund has underperformed the market significantly.

Video Explaining the Differences

Etymology

"Data" comes from a singular Latin word, datum, which originally meant "something given." Its early usage dates back to the 1600s. Over time "data" has become the plural of datum.

"Information" is an older word that dates back to the 1300s and has Old French and Middle English origins. It has always referred to "the act of informing," usually in regard to education, instruction, or other knowledge communication.

Grammar and Usage

While "information" is a mass or uncountable noun that takes a singular verb, "data" is technically a plural noun that deserves a plural verb (e.g., The data are ready.). The singular form of "data" is datum — meaning "one fact" — a word which has mostly fallen out of common use but is still widely recognized by many style guides (e.g., The datum proves her point.).

In common usage that is less likely to recognize datum, "data" has become a mass noun in many cases and takes on a singular verb (e.g., The data is ready.). When this happens, it is very easy for "data" and "information" to be used interchangeably (e.g., The information is ready.).

References

  • Data - definition and examples on Wiktionary.org
  • Information - Wiktionary.org

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.

Interested in learning more about how you can harness data (and the information gleaned from it) in a knowledge management strategy?

Get our “Ultimate Guide to a Modern Knowledge Management Strategy.”

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.
  • A customer’s response to an individual customer service survey is a point of data. But when you compile that customer’s responses over time—and, on a grander scheme, multiple customers’ responses over time—you can develop insights around areas for improvement within your customer service team.
  • The number of likes on a social media post is a single element of data. When that’s combined with other social media engagement statistics, like followers, comments, and shares, a company can intuit which social media platforms perform the best and which platforms they should focus on to more effectively engage their audience.
  • On their own, inventory levels are data. However, when companies analyze and interpret that data over a range of time, they can pinpoint supply chain issues and enhance the efficiency of their systems. 
  • Competitors’ prices are individual data elements, but processing that data can reveal where competitors have an advantage, where there may be gaps in the market, and how a company can rise above its competition.

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.

Is found in information that is dependable and free from error or bias?

Information is reliable if it is free from error or bias and accurately represents the events or activities of the organization. Information is complete if it does not omit important aspects of the underlying events or activities that it measures.

In which transaction cycle would information for inventory purchases be most likely to pass between internal and external accounting information systems?

The correct option is B) “The expenditure cycle” Yes, the expenditure cycle provides the information for the purchase of inventory which is most likely to pass in between internal and external AIS (Accounting Information System).

What is a key decision that needs to be made with regards to acquiring equipment?

The location is considered to be a key decision that need to made regarding acquiring equipment because depending on the size and the weight of the equipment the strength of the building's foundation say if the machine needs to be fit below ground level, the carrying cost based on the location also can add up to the ...

Which of the following is an example of an AIS output?

Internal documents are another form of output from an accounting information system. Examples of internal documents include credit memorandums, receiving reports, production routing documents, and production scheduling documents.