Data Versus Information and It’s Imperative to Know the Difference

Dr. Negus Rudison-Imhotep | Contributor on topics related to memory and memory building

Data and information are connected. Data usually means raw data or in unprocessed form. It is the basic form of data that hasn’t been analyzed or processed in any manner. Once the data is analyzed, it is considered as information.

Want to learn more about storytelling? Start by downloading the first chapter of The Storytelling Mastery.

Information is “knowledge communicated or received concerning a particular fact or circumstance.” Information is a sequence of symbols that can be interpreted as a message.

It provides knowledge or insight about a certain matter or subject. Data is raw data. It represents ‘values of qualitative or quantitative variables, belonging to a set of items.’ It may be in the form of numbers, letters, or a set of characters.

It is often collected via measurements. In data computing or data processing, data is represented by a structure, such as tabular data, a data tree, a data graph, etc.

Data and information are interrelated. They are often mistakenly used interchangeably. It represents ‘values of qualitative or quantitative variables, belonging to a set of items.’ It may be in the form of numbers, letters, or a set of characters. It is usually generated via measurements.

In data computing or data processing, data is represented by a structure, such as tabular data, a data tree, a data graph, etc.

See also Harnessing AI Power: Driving Business Growth through Data, Personalization, and Automation

The reliability of data depends on its ethical sources and continuous updating. It is prescribed in the form of data catalogs, datasets, data tables, data reports, averaging data, and other resources.

Information is “knowledge that is sent and received related to a particular fact or situation.” Information is an array of symbols that can be processed as a message. It provides knowledge or insight about a certain matter.

Information can be recorded as signs or transmitted as signals. It answers certain questions like how the information is affected, what are the benefits of information, who are its users, where exactly it is required etc.

Information is the message that is being conveyed, whereas data are plain facts. Once the data is processed, organized, structured, or presented in a given context, it can become useful.

Then data will become information and knowledge. It must be in simple form and free from biases. For example, data “gross Sales figures for 2013 was 10 million dollars whereas for 2013 it was 7.5 million dollars” gives a conclusion for comparison of two years sales volume for a marketing department in an organization.

For example, a manager must check why quality has fallen in the last month. Do we need to hire more numbers of staff or to lay off or predict consumer demand for the future?

See also Cultivating Consumer Trust: The Power of Transparency in Agribusiness Storytelling

For all this data is required from which we need to screen out information for making decisions. It helps in making decisions only but also at the right time thereby increasing the scope of improvement.

Components of Data and Information

Uses and applications:

These days computers and information processing are everywhere. From our perspective, the essential element of management is information processing, and mainframes are expected to heavily influence management.

• Nowadays, computers and information processing are ubiquitous. From our standpoint, information processing is a crucial aspect of management, and therefore, computers are anticipated to significantly impact management practices.
• The advantages of vast data systems are especially visible in the relationship between programs and costs. For appropriate, cost-effective, and timely decisions about affected role hospitals, and programs to be made, accurate and complete information must be widely available to the many users of hospital data, such as the research team or community, hospital administrators, board members, policymakers, improvement teams, potential investors, and the public.

Data is stored and utilized in all types of organizations to facilitate decision-making. In accounting, managers use data to calculate figures and numbers. In HR, it is used for maintaining employee records.

The sales and marketing departments use data to track customer records, sales, budgets, and more. Examples include banks, insurance companies, utilities, and government agencies like the IRS and the Social Security Administration.

It is the responsibility of management to continually update and maintain data quality.

• The accuracy of collecting and distributing information relies on the quality of the data. During this process, data can become distorted, sometimes intentionally. Employees are often asked to summarize data and report it to their supervisors. At each stage of this screening process, crucial information may be omitted, reducing the overall reliability. This intentional omission is one form of data distortion.
• Decision-making and policy formulation rely heavily on data and its interpretation. Management bases its decisions on data gathered both internally and externally, including sources such as the Internet, external partners, and market surveys.
• The scope of information management includes both information technology and data management. It encompasses several dimensions, including availability, organization, and application.
• The Commission, various governments, and other organizations maintain active websites on the Internet that offer a wide range of information and services, including data on healthcare, employment, population, the economy, and more.

Uses of Data and Information with examples:

Converting data to information in Human Resource

For many HR departments, data presents a significant opportunity. HR teams gather data to illustrate the impact of employee policies and investments on the business.

See also Brain Re-Engineering Concept and Reimagination: Strategy for Early Career Academics in Agriculture and Food Systems Research

By analyzing and interpreting this data over time, HR can forecast future workforce needs and develop effective strategies for recruitment, selection, HR budgeting, and investments in training and development, compared to the previous year.

In Organizations

One of the main reasons that organizations collect data is to monitor and improve performance. Healthcare data are raw healthcare facts, generally stored as characters symbols, words, measurements, and statistics, while healthcare information is processed from healthcare data.

Difference Between Data And Information Origin

The term ‘data’ originates from the singular Latin word ‘datum,’ meaning ‘something given.’ Its usage can be traced back to the 1600s. Over time, ‘data’ has evolved to be recognized as the plural form of ‘datum’.

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

Other Differences

• Data is used as input for the computer system. Information is the output of data.
• Data is unprocessed facts and figures. Information is processed data.
• Data doesn’t depend on Information. Information depends on data.
• Data is not specific. The information is specific.
• Data is a single unit. A group of data that carries news and meaning is called Information.
• Data doesn’t carry a meaning. The information must carry a logical meaning.
• Data is the raw material. Information is the product.

Examples of Data and Information

• The temperature readings collected globally over the past century constitute data. When this data is organized and analyzed to reveal a rising global temperature trend, it becomes 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.

Conclusion

Essentially, information is the communicated message, while data are simple facts. When data is processed, organized, structured, or presented within a specific context, it becomes valuable. At this point, data transforms into information and eventually into knowledge.

Data needs to be updated regularly to increase its efficacy. Second, organizations need to understand the importance of data as a business strength, to make decisions based on facts, give in-depth knowledge, and thus helpful in taking some action.

See also A Comprehensive Guide for Data and Monitoring Systems in Cassava Farming

The global temperature readings gathered over the past century represent data. When this data is organized and analyzed to uncover a trend of increasing global temperatures, it transforms into information.

References

Amidon, D.M. (1997) Innovation Strategy for the Knowledge Economy: The Ken Awakening; Butterworth-Heinemann, Newton, MA, USA.

Davenport T.H. and Prusak L. 1998: Working Knowledge: How Organizations Manage What They Know. Boston, MA: Harvard Business School Press.

Karen A. Wager, Frances Wickham Lee, John P. Glaser, Health Care Information Systems: A Practical Approach for Health Care Management.

Liew, A. (2007). Understanding data, information, knowledge, and their inter-relationships. Journal of Knowledge Management Practice, 8(2), 1-16.

Moubayed, A., Injadat, M., Nassif, A. B., Lutfiyya, H., & Shami, A. (2018). E-learning: Challenges and research opportunities using machine learning & data analytics. IEEE Access, 6, 39117-39138.

Rao M. (2005) Knowledge Management Tools and Techniques.

Stankosky M. (2005) Creating the Discipline of Knowledge Management: The Latest in University Research, Elsevier

Literature Review

Kogut and Zander (1992) – Information as “knowledge which can be transmitted without loss of integrity.”

Wiig (1993) – He has suggested that the information is, “facts organized to describe a situation or condition.

Andrew P. Garvin (1996) – He has suggested that “data organized to become information” and “information put into context to become knowledge.”

Allie (1997) – Opined that “data float in a larger sea of information, and data become information through linking and organizing with other data.

Information becomes knowledge when it is analyzed, linked to other information, and compared with what is already known”.

Want to learn more about storytelling? Start by downloading the first chapter of The Storytelling Mastery.