Information is everywhere.
We have information on the menus at our restaurants,
in the books in our libraries, and on street
signs while we’re driving.
But what exactly is information in the context
of data science?
Information is something that reduces uncertainty
about our world.
It is the answer to questions like who, what,
where, how many, or how much.
Essentially, information provides clarity
about the world we live in.
Information is created from data.
We create information by organizing, analyzing,
and interpreting data.
Organizing, analyzing, and interpreting data
gives it context and meaning.
This additional context and meaning is essentially
what distinguishes raw data from information.
For example, imagine that our doctor has a
recorded a history of our normal body temperature
over the past few years.
They analyze the historical data and computes
that our average (or normal) body temperature
This average temperature of 37°C is what
we call information.
Information is more meaningful than the individual
data points that were used to create it.
This makes information quite useful on it’s
However, information can also be used to create
something more powerful
it can be used to create knowledge.