[Video Transcript] Business Analytics: Decision Making Using Data at Cambridge
Hello, my name is Nektarios Oraiopoulos. I'm a University Lecturer in Operations and Technology Management at the University of Cambridge Judge Business School. My research aims to understand how organizations make high-stake decisions, such as whether to invest in a new project or when to terminate a project that is not performing well. What data can organizations leverage to become more innovative and what organizational structures should they put in place to enable a sound decision-making process?
Over the past few years, I worked on those topics with a number of leading organizations from various industries and sectors, including Astra Zeneca, British Telecom, HSBC, Johnson & Johnson, and the Abu Dhabi Police Force.
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Hello, my name's David Stillwell and I'm a University Lecturer in, deep breath, Big Data Analytics and Quantitative Social Science at the University of Cambridge's Judge Business School. So, what that rather long job title means is that I study the links between big data and psychology. My research with six million social media users found that the computer can predict a user's personality as accurately as their spouse can and that personalizing an advert to the recipient's psychology is more effective than just generic advertising.
I have also published research using various big data sources such as credit card data, where I showed that spending money on products and services that match one's personality leads to greater life satisfaction, and with social media data, where I found that people tend to date other people who have a similar personality, and also that people who swear seem to be more honest.
Throughout the program, we will draw from industry examples such as the UPS ORION Project, the Google Oxygen Study, and the hacking of Talktalk, a large telecommunications company.
Specifically, in this program, you will learn how the decision-making process works and how to identify and overcome biases in decision-making. About data mining and cleaning, the basic statistical measures used in descriptive analytics, and how to use APIs. What big data is, what it means, and the challenges that accompany it. How to make successful experimentation work and hear some success stories of businesses who use it to their benefit. How to use machine learning tools to gain insights into data. How to make business decisions, once you have insights into the data. How to overcome organizational and behavioral biases that can affect the decision-making process. And the ethical and legal challenges of gathering, storing and using data.
In addition to the video lectures, the program gives you the opportunity to engage in hands-on assignments that help you apply the concepts. You'll also have the opportunity to participate in peer discussions and live webinars with us. So come join us for an exciting opportunity as we explore the many different applications and challenges of using data to make decisions.
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