Analytics requires context
Data is messy, complex & unstructured, because the people who create data are correspondingly messy, complex & unstructured.
Visual, textual, video, & audio data is created by people, & require context to comprehend.
On its own, data does not create meaning.
We do.
We have a responsibility to spend more time focusing on critical thinking.
Spending precious time on the humanities, sociology, social sciences, rhetoric, philosophy, & ethics give us valuable context that is so important for interpreting data.
If we don’t take time to create the right context, & we process exabytes of data in seconds, we will make bad decisions more quickly & more efficiently with greater negative impact.
We cannot be passive consumers of data & technology.
We shape the role data plays in our lives & businesses, & the way we make meaning from it.
To do this, we have to pay as much attention to how we think as how we calculate.
Analytics means we have to move past counting things, to understanding them.
Visual, textual, video, & audio data is created by people, & require context to comprehend.
On its own, data does not create meaning.
We do.
We have a responsibility to spend more time focusing on critical thinking.
Spending precious time on the humanities, sociology, social sciences, rhetoric, philosophy, & ethics give us valuable context that is so important for interpreting data.
If we don’t take time to create the right context, & we process exabytes of data in seconds, we will make bad decisions more quickly & more efficiently with greater negative impact.
We cannot be passive consumers of data & technology.
We shape the role data plays in our lives & businesses, & the way we make meaning from it.
To do this, we have to pay as much attention to how we think as how we calculate.
Analytics means we have to move past counting things, to understanding them.