In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies.
Risk Metrics: Leverage and Reputational Risk
Skills You'll Learn
Data Analysis, Business Analysis, Business Analytics, Business Process
Reviews
It's a great course because even it's based on theory not practical(Which cover in next courses in specialization) but still, at final assignment submission, you feel great that you tackle a problem.
It's the first course from the specification, which makes us better understand the necessary business metrics for data-driven companies, and it is a good entry for following modules. Help me a lot.
Welcome! This week we will explore business metrics - the critical numbers that help companies figure out how to survive and thrive. Inside every pile of data is a vital metric trying to get out! By the end of this week, you will be able to: distinguish business metrics from mere business data; identify critical business metrics such as cash flow, profitability, and online retail marketing metrics; distinguish revenue, profitability and risk metrics; and distinguish traditional from dynamic metrics. Included in this week’s course materials is a Cash Flow and P&L statement for Egger’s Roast Coffee, as a supplemental document, so be sure to review it carefully and refer to the glossary for key information.
Taught By
Daniel Egger
Executive in Residence and Director, Center for Quantitative Modeling
Jana Schaich Borg
Assistant Research Professor
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