The goal of this course is to introduce the students to key ideas about data-intensive business decision-making. The ideas explored in the course include: 1) Understanding that the questions a business needs answered precedes the collection and analysis of data. 2) The difference between what the data "say" and what the data "mean." 3) Understanding and measuring randomness and its implications. Different sources of randomness (inherently random outcomes vs. measurement errors). 4) Introduction to standard questions and analyses that businesses need to address. 5) Understanding traps and biases in the data and their implications on the analysis. 6) Difference between various modelling approaches. 7) In sum, this course is designed to get you excited about how you can use data and analysis to help a business make better decisions.