What is the purpose of collecting data, creating
information, and acquiring knowledge?
Essentially, what makes data so important
in data science?
Data, on it’s own, is useless.
However, it can be a stepping stone to achieve
a goal or an objective of some kind.
In order to achieve our goal we need to transform
data into something that is actionable.
We need to transform our data into actionable
We do this through the following process:
First, we collect data by observing the world
and recording our observations.
Next, we organize, analyze, and interpret
our data to create information.
Then, we combine this information with other
information to create knowledge.
Next, we use this knowledge and new information
to make an informed decision
about which action to take.
Then, we can take action with the confidence
that we have increased the likelihood
of achieving our goal.
In data science, we refer to this process
as “transforming data into actionable insight”.
In the world of business, this is often referred
to as “data-driven decision making”.
In our daily lives, we simply refer to this
process as “intelligence”: the use of knowledge
and new information to make rational decisions
about actions that will maximize our chances
of achieving a goal.