How to talk about Big Data without doing Big Data. What is Big Data? Data science? Machine Learning? AI?

Learn about the sources of data, the analytical methodologies, and the business applications. Understand the jargon and acronyms. Appreciate the promises and the challenges. Feel confident when talking to your data team.

Data visualization – when done right – can transform not only the way you present results to stakeholders in your organization, but also the way you explore and analyze the data itself.

Dynamic visualization helps researchers find and construct a narrative around linkages between variables in even the most complex data sets.

You’ll learn how to weave together analytics and data visualization to produce graphs that make an impact.

In the Big Data age, all workers must learn how to make and debate arguments driven by data. Big data have spurred more debate, not less.

Using the Harvard case method, learn how to interpret Big Data analyses without needing to learn math. Finally understand key concepts such as sampling bias, statistical variability, statistical significance, statistical adjustments, and statistical models using case studies and in-class discussion.