Business Analytics for Data-Driven Decision Making
Learn how to lead your firm to make better business decisions using analytic methods and create competitive advantages from data.
Virtually all managerial and leadership positions in the digital economy increasingly rely on data-driven decision making. Recent studies have shown companies who adopt “Data-Driven Decision Management” achieve significant productivity gains over other firms.
Having a solid grasp of the end-to-end process of making effective decisions with data will give you an edge, both in performing such analyses yourself, as well as in effectively managing teams of business analysts and data scientists.
In this course, part of both the Digital Leadership and Digital Product Management MicroMasters programs, you will learn the tools and techniques to become a data-driven or “evidence-based” manager.
You will learn the process of reframing a business question as a data question, reasoning about what data might be of assistance and how to obtain it, integrating and cleaning the data, performing the analysis, deriving and communicating insights from the analysis, and building the managerial culture to operate in this way and create competitive advantages from enterprise data.
This course is unique in the sense that it aims squarely at the needs of a manager in an analytically focused enterprise by providing both a hands-on introduction to the concepts, methods and processes of business analytics as well as an introduction to the use of analytics as the basis for creating a competitive advantage.
Completion of this course requires the use of Microsoft Power BI Desktop. Unfortunately, there is currently no version of Power BI Desktop for macOS or Linux operating systems. We encourage learners to secure access to a Windows environment, but if that is not possible, macOS and Linux users can run Power BI Desktop in a virtual Windows environment. The course provides steps for installing such an environment.
What you’ll learn
- Key analytic technologies and techniques, e.g. predictive modeling and machine learning, and how these can play a role in managerial decision making
- How to effectively manage the analytical processes and use the results of these processes as the basis for making informed, evidence-based decisions
- How companies can use analytics as the basis for creating value