Data, Information, and Knowledge.
When discussing Business Information Systems, you'll often hear people throw around the words 'Data', 'Information', and 'Knowledge' almost interchangeably. However, the truth is that these three words have some significant key differences, especially when talking about information systems. Understanding the relationship between the three will greatly aid us in our ability to make powerful, informed decisions.
Let's start with Data. Data is what we would refer to as 'raw facts' or 'the facts of the Universe'. Data is the log of immutable information over many different points in time. Data is passive and inert. We can look at Data as a series of 'symbols and signs', raw observations of facts as they exist in our world. Generally, we can consider something a fact if it is verifiable, observable, and true. However, these raw facts, when presented, offer little useful insight that we can use towards our own benefits. That's where Information comes in.
Information is the collection and organization of data in such a way as to make data meaningful to our needs. Information seeks to answer questions we have about processes in the world. Information is the answers to whichever 'what, where, when, how, and why' queries we might have. We filter data and process it, and the resulting information can then be applied towards finding solutions. Information is data with meaning. Interestingly, an important distinction between Data and Information is that Data can never be wrong, while Information can. Data is always true but can change over time. Information is a log of data at a given instance in time. I can be 25 and 35 years old, but not both at the same time. The data of my age changes over time, but there could exist two separate records (Information) of my age that would conflict with each other. However, we still need Information in order to inform knowledge.
This brings us to Knowledge. This is the most elusive of the three concepts, and certainly the hardest to define. Knowledge is in some ways a map of the brain. It is the neural connections between different nodes of information in our minds that are able to connect these nodes into something meaningful. Knowledge represents the collection of Information and then the application of that Information towards an end. Currently, only the brain is able to parse Information in such a meaningful way, although great strides are being made in teaching computers how to mimic this mental behaviour. There have been huge advances in Machine Learning recently that are teaching computers how to learn. Upon learning, a machine could eventually make the jump towards understanding. But for now, only we possess the ability for Knowledge
I only mentioned three concepts in my title, but in truth, there are four. The fourth concept is Wisdom. This one is not as interchangeable as the other three, but it is the end game that all Data, Information, and Knowledge funnel towards. Wisdom is the ability to take Knowledge, and apply discretion to it. Wisdom is understanding when to use Knowledge, how to use Knowledge, or why to use Knowledge. It is Wisdom that we strive to enhance. Wisdom, in essence, understanding all aspects of stimulus that came before it, is what allows us to make impactful and intelligent decisions. Wisdom is the holy grail that machine learning seeks. For now, however, computers remain only a tool to help us collect Data in a more efficient way, parse out meaningful Information from that data, and bolster our Knowledge so that we may be able to make the wisest decisions possible.