In this course, you'll learn to contextualize qualitative and quantitative data to improve business decisions. You'll explore data collection tools, compare data-driven and data-inspired approaches, and understand why analysis can sometimes fail. You'll examine performance metrics and use data visualization to communicate the story behind the numbers. You'll study dashboard types, design principles, and mathematical thinking strategies to spot patterns to solve problems. Finally, you'll practice selecting the right analytical tools for different datasets based on their characteristics.

By the end of this course, you will be able to: • Discuss the importance and benefits of dashboards and reports to the data analyst with reference to Tableau and spreadsheets • Explain the difference between quantitative and qualitative data including reference to their use and specific examples • Compare and contrast data-driven decision making with data-inspired decision making • Discuss the use of data in the decision-making process • Differentiate between data and metrics, giving specific examples • Demonstrate an understanding of what is involved in using a mathematical approach to analyze a problem