Making an informed data-driven decision is important. In this course, Approaches to Data Enabled Decision Making, you’ll learn to structure decision-making in an enterprise setting to be grounded in data. First, you will explore the different types of data-enabled decision-making such as data-inspired, data-informed, and data-driven decision making and understand the similarities and differences between these. You will also learn the basic steps involved in data-driven decision-making and how they can be applied in an organization. Next, you will explore some common frameworks for data-enabled decision making such as the BADI framework, multiple-criteria decision making using goal programming, and the analytic hierarchy process. You will also learn how to relate to workflows in analytics, such as CRISP-DM, and the build-test-deploy lifecycle of an ML model. You will also study Porter’s five forces framework to analyze competitive forces in any industry. Finally, you will explore real-world organizational case studies that use data to structure both tactical and strategic decisions. Case studies will cover the hospitality industry, a financial management firm, and a wedding and wine event management company. When you’re finished with this course, you’ll have the skills and knowledge of data-driven decision-making needed to effectively structure and drive decision-making in your organization.
Author Name: Janani Ravi
Author Description:
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing … more