When Does Data Become Knowledge?

Within the modern workplace, we talk about “knowledge management” when, in reality, we’re mostly talking about “data management.” There’s a big difference between the two, and yet many use the terms interchangeably. My question is: When, exactly, does data become knowledge?

It’s an interesting topic of discussion, and I’d be interested to hear different opinions.

I think of data as a collection of raw facts, figures, and statistics that have been gathered through observation, measurement, or research. Data can be in various forms such as numbers, text, images, videos, or sound recordings, and it can be structured or unstructured. Structured data is organized and formatted in a specific way, such as in a spreadsheet or database, whereas unstructured data is not organized in a specific way and may include text files, emails, or social media posts. Furthermore, data is usually collected for a specific purpose and can be analyzed to extract insights or patterns that can be used to make informed decisions.

The mistake that people make is thinking data is knowledge. Data alone does not provide much meaning or insight without proper processing, analysis, and interpretation. I often talk about the problem of “management by spreadsheet” or, in other words, making management decisions based on data in spreadsheets, often without proper context or analysis.

Knowledge, on the other hand, implies a deeper level of understanding that goes beyond just the raw facts and information. It is a result of applying human interpretation, experience, and expertise to information to make sense of it in a meaningful way. Knowledge involves the ability to recognize patterns, connections, and relationships between different pieces of information, and to draw conclusions or make decisions based on that understanding. It is a cognitive process that involves critical thinking, analysis, and judgment.

Knowledge can be explicit, meaning it is formalized and documented in some way, such as in a book, a database, or a manual. Alternatively, it can be tacit, meaning it is more personal and subjective, and is based on an individual’s experiences, insights, and intuition.

Going back to my original question: When does data become knowledge?

Data becomes knowledge when it is processed, analyzed, and interpreted in a way that adds context and meaning to the information. Knowledge is a deeper understanding of data that goes beyond just the raw numbers or facts.

For example, if you have a dataset or a spreadsheet of monthly sales numbers, that data alone is not very informative. But if you analyze the data to find patterns and trends, and then interpret those patterns to make decisions about how to improve sales, then that information becomes knowledge. In other words, knowledge is the result of applying human expertise and interpretation to data in order to extract meaningful insights and understanding. It requires critical thinking, analysis, and judgment to turn data into knowledge.

So…when you talk about knowledge management, are you really talking about collecting, combining, and storing numbers, text, images, videos, and sound recordings, whether structured or unstructured? Or are you using that data to make informed decisions and take actions that are based on a deeper level of understanding and insight?