Data science has been called “the sexiest job of the 21st century” and with good reason—the size and breadth of our data is growing exponentially, making our ability to understand that data more and more challenging. This session defines data science, describes how it is similar to and different from related analytics disciplines, and the key concepts every data scientist needs to know.
In this overview, data science will be described in a project-oriented framework. Each project must define objectives, collect and integrate data, prepare it for analysis, perform the analysis, and deploy the results. Whether the end-goal of the project is reporting, visualization, descriptive modeling, or predictive modeling, the same principles apply. For each stage, key principles will be described and real-world examples will illustrate the meaning of these principles.