Data, Information, Knowledge, and Data

Data, Info, or Knowledge?

What is data? It’s a set of discrete, objective facts about events. It could be one transaction in your retail store, one visit to your website, or an article in your pile of RSS reader subscription. Why is that data? There are at least 4 reasons why data is data. Let’s take an example of site visit event, and why do I think that it is data.

• Everyone else is doing it. Tell me if there is any site that is not counting their visitor? Maybe there is one or two, but if they seriously think about doing something significant, business or so with the website will likely to count their visitors.
• Voluminous. The more your site’s subscribers, the more visitor you have, and that is a significant measure that what you have is data.
• Automatic capture. You can put a counter in your website, that is increased for every visit. You can ask help from SiteMeter or Google Analytics. You can use their data, but unless you do more things with it, it’s simply automated capture that is meaningless to you.
• Doesn’t answer substantive question. You may have the visit info, but merely data will not answer substantive questions, such as what profile are your visitors, where do they come from, why do they buy or why don’t they buy your product and services, what are they interested in, and so on.

Information is simply data that is put with more meanings into it. Let’s come back to our site visitor example, Google Analytic gives us a much more useful information based on the visitor data that it collected. So here is what they do with it, the data is…

• Contextualized, as a service provider, Google doesn’t just give and present data aimlessly. It provides the data as a service that they provide to site owners. They put more information into the visit data that they gathered to meet the common information that site owners need. And how they do it can be explained further to the following points.
• Categorized, the traffic is differentiated into many classification, some examples are their location and traffic source. Taking traffic source as an example, the traffic is differentiated between direct traffic, referring site, and search engine. Again another value it contributed to their users to analyze the traffic further.
• Calculated, they calculated more than just number of visit. They have bounce rate, the rate of people going off the site soon after they come. They also have page views to count the number of views per visit.
• Condensed, the data has been condensed into a summary format. By default it summarized your data in monthly manner, but you have the ability to adjust the period longer or shorter as needed.

Now, let’s talk about knowledge. The Master course I’m attending took almost an hour to explain what is knowledge. The lecturer, Prof. Lee Chu Keong gave us the definition from various type of people. I won’t go through that here, but let us explore more about how can we transform information to knowledge.

• Comparison, what kind of situation or impression does that information give us, compared to other situations we have known?
• Consequences, how will the information affect our decision and action?
• Connection, how does the information relate to the others that we have received?
• Conversation, what do other people think about the information?

As you see, knowledge is a personalized information. Only when you take an information, reflect upon it, compare and relate it against your experience and others, then it will become knowledge. That is why, you should never say that a book is knowledgeable, because a book does not contain knowledge. Knowledge is contained within a person. And yes, you can only attribute “knowledgeable” to a person.

And back to the data again. No, it’s not meant to be a repetition. It was meant to give you one idea and one warning. Let’s start with the idea first.

These data, information, and knowledge are practically a cycle. Tuomi raised the idea of reverse knowledge hierarchy, where people must have knowledge before they can find out the data that they need to gather. Let’s take an example as an internet marketer, you certainly need to have some kind of knowledge about internet marketing, to know what kind of information you need to collect, and how you can collect those data to improve your marketability and profit. That pattern, knowledge -> information -> data is exactly the reverse knowledge hierarchy Tuomi was referring about. So again, yes, it’s really a cycle of knowledge.

Now, let’s finish this article with the warning. Besides how knowledge can give us insights on the value-added information, knowledge can also move down the value chain. It can turn into information and eventually data. That happens when we are in the information overloaded mode.

Earlier I mentioned that an article in RSS reader could be data. Why did I say that? Don’t get me wrong, that article could be contextualized, categorized, calculated, and condensed information. However, when we have too much knowledge, we will go through a process that Davenport and Prusak will call as de-knowledging. The knowledge and information abundance that we have will become data due to its voluminous tendency.

And yes, this is an era of participation, era of Web 2.0 that everyone can become a producer and publisher, from thoughts, words, pictures, audios to videos. This is an era from which any amateur can join the crowd to have their own say and contribution. This is the danger that Andrew Keen captured in his book The Cult of The Amateur.

In this era of exploding media technologies there is no truth except the truth you create for yourself.
~Richard Edelman (Edelman PR) quoted by Andrew Keen

This age has become a real threat to knowledge, and this open up the importance of knowledge management in the world. How do we ensure that what we have is knowledge, not to be overloaded with too much information, but how can we capture the significant and authentic voice in the crowd? These are the questions that KM needs to answer in this era. And let’s explore with me in this blog. Share your thought if you are reading this.

Best regards,
Robert