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 insight. 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.