Distinguishing Data, Information, and Knowledge: Concepts & Examples

This discussion post highlights the key differences between data, information, and knowledge using examples such as McDonald's restaurant data, world population estimates, and Amazon's sales figures. Raw data, like the number of McDonald's restaurants in the US, becomes information when context is added. Knowledge is then derived by analyzing related information to answer specific questions, such as estimating market share or predicting population growth. The post emphasizes that information is a group of related raw data required to gain knowledge on a specific topic, and it illustrates how Amazon's market share can be estimated from sales data and user search patterns. The post concludes by highlighting the difference between obtaining raw data and deriving meaningful insights from it, referencing studies on knowledge management and big data.

Runninghead: DATA,INFORMATION AND KNOWLEDGE
DATA, INFORMATION AND KNOWLEDGE
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1DATA, INFORMATION AND KNOWLEDGE
Hi all!
In this discussion forum post, I will highlight on the key differences between data, information
and knowledge. As we know, McDonald’s is one of the biggest restaurant chains globally. It has
14,350 restaurants in US alone. Here, 14350 is a raw data without meaning. When I read the full
line, I get the information about the restaurants. Now when I learn that this company has 36,000
plus restaurants worldwide, I can then estimate the market share of US (7.3%) but still have no
idea about the global share, as this knowledge will depend upon data from other global restaurant
chains as well. A group of related raw data is called information and is required to gain the
knowledge or answer a specific topic. For another example, it is mentioned that the world
population will increase from 7.3 billion in 2015 to 9 billion in 2042. Estimating this data,
depends upon information which comprises of the related expected population figures in 2050 of
major population countries like China(1.4 billion),India(1.69 billion),US(439 million) and
Indonesia(313 million). This information is enough to predict the 9 billion figure (knowledge). In
another example, Amazon’s sales in 2014 was 88.99 billion dollars. This is a raw data or a fact.
Amazon had an increase in sale of 14.5 billion dollars in that year. Walmart’s sales also
increased by 3 billion dollars that same year. This two data are related and gives us the
information how these two companies fared in 2014. Total online sales in 2014 globally was 300
billion dollars. Now, with this information I can estimate Amazon or Walmart’s market share in
2014. Similarly in 2009, 18% of users searched in Amazon for products and 24% in Google. In
2014, 39% used Amazon and 11% used Google. Hence, from studying these raw data I can gain
the knowledge that Amazon leads in this segment now. Thus, there is a big difference between
getting raw data from Google and estimating it.
Thank you!

2DATA, INFORMATION AND KNOWLEDGE
References:
Cooper, P. (2017). Data, information, knowledge and wisdom. Anaesthesia & Intensive Care
Medicine, 18(1), 55-56.
Hitt, M. A., Ireland, R. D., & Hoskisson, R. E. (2016). Strategic management: Concepts and
cases: Competitiveness and globalization. Cengage Learning.
Pauleen, D. J., & Wang, W. Y. (2017). Does big data mean big knowledge? KM perspectives on
big data and analytics. Journal of Knowledge Management, 21(1), 1-6.
What is Knowledge in the Age of Big Data? | Timandra Harkness | TEDxSquareMile. (2019).
Retrieved from https://www.youtube.com/watch?v=tdilkRC4YVw&t=95s