When might data analytics be appropriate for making a decision?

1. When data is dirty and making an unethical decision?

2. When data suggest making an unethical decision

3. When data does not exist in a decision context

4. When data cannot be reliably measured

Which of the following reasons is not a reason why interpreting data analytics result is difficult?

1. Humans can experience information overload in complex situations

2. Humans often mistake correlation for causation

3. Humans have biases that may cause them to misinterpret data

4. Humans rely on automation that increases the speed at which data is analyzed

A company upgraded production machinery to transmit data to the data warehouse about the fit tolerance for assembled part of each unit produced as the measures are taken. Before the upgrade, data was transmitted at the end of a production run. The upgrade presents an:

1. Data velocity

2. Data volume

3. Data veracity

4. Data variety