Business Analytics (Online): Create Value Through Data AnalysisNEW

Select
Date(s)
October 5–November 23, 2022
Cost
$1,989
CIBE Credits
1
Format
Online
Location
Online

Business Analytics (Online): Create Value Through Data Analysis


Select
Date(s)
October 5–November 23, 2022
Cost
$1,989
CIBE Credits
1
Format
Online
Location
Online

Overview

Impact

Highly data-driven organizations are three times more likely to report significant improvement in decision-making. Source: Think with Google
3X
of top-tier data companies with a data culture that are meeting or exceeding their revenue targets. Source: Alation State of Data Culture Report
75%
of workers fully confident in their data literacy skills. Source: Forbes
21%

Participant Profile

Program Structure

1. Introduction to Business Analytics

Introduces business analytics and its main levers that organizations use to capture value through it.

2. Leading Analytics

Review a common business analytics tool to leverage the data and for predicting outcomes: Logistic Regression.

Program Faculty

Omar Besbes - Columbia Business School

Omar Besbes

Vikram S. Pandit Professor of Business

Omar Besbes - Columbia Business School

Omar Besbes

Vikram S. Pandit Professor of Business

Omar Besbes's primary research interests are in business analytics regarding the area of data-driven decision-making with a focus on applications in e-commerce, pricing and revenue management, online advertising, operations management, and general service systems. He has taught core MBA courses in Operations Management and Business Analytics, an MBA elective on advanced Business Analytics, as well as various PhD seminars on stochastic models, revenue management, and data-driven decision-making. He is a recipient of the Dean's award for teaching excellence in the core at Columbia Business School. A graduate of Ecole Polytechnique (France), he holds an MSc from Stanford University and a PhD from Columbia University.

Mark N. Broadie - Columbia Business School

Mark N. Broadie

Carson Family Professor of Business

Mark N. Broadie - Columbia Business School

Mark N. Broadie

Carson Family Professor of Business

Professor Broadie is an Academic Advisory Board Member for the Program for Financial Studies. His research interests include the pricing of derivative securities, risk management, and, more generally, quantitative methods for decision-making under uncertainty. Broadie is the financial engineering area editor of Operations Research and serves on the editorial boards of Finance and Stochastics, SIAM Journal on Financial Mathematics, and Computational Management Science. He was previously editor-in-chief of the Journal of Computational Finance. Professor Broadie received two Dean's awards for teaching and has given seminars and courses for financial professionals throughout the world. He is the vice chairman of Enterprise Risk Management Institute International (ERM-II), a non-profit organization dedicated to promoting education, research, and training of enterprise risk managers.

Charles Daniel Guetta - Columbia Business School Executive Education

Charles Daniel Guetta

Associate Professor of Professional Practice

Charles Daniel Guetta - Columbia Business School Executive Education

Charles Daniel Guetta

Associate Professor of Professional Practice

Daniel Guetta is an Associate Professor of Professional Practice at Columbia Business School and Director of the Business School's Center for Pricing and Revenue Management. He is also Director of the Business Analytics Initiative at the Columbia Business School and Columbia Engineering. Professor Guetta’s research focuses on the ways companies can harness the power of data and analytics to drive value. In addition to teaching business analytics courses including programs in data science, pricing, supply chain management, and technical tools such as python and cloud computing, he has authored award-winning case studies in the area with a number of companies and co-authored the book "Python for MBAs.” Prior to joining the faculty at Columbia, he was a data scientist and engagement manager at Palantir Technologies, where he worked with clients around the world in fields ranging from finance to pharmaceuticals to help them solve their hardest problems using data. He completed his undergraduate studies in physics and mathematics at Cambridge and MIT and holds a PhD in Operations Research from the Columbia Business School.

Ciamac C Moallemi - William Von Mueffling Professor of Business

Ciamac C. Moallemi

William Von Mueffling Professor of Business

Ciamac C Moallemi - William Von Mueffling Professor of Business

Ciamac C. Moallemi

William Von Mueffling Professor of Business

Ciamac C. Moallemi is the William Von Mueffling Professor of Business in the Decision, Risk, and Operations Division of the Graduate School of Business at Columbia University. He also develops quantitative trading strategies at Bourbaki LLC, a quantitative investment advisor. A high school dropout, he received SB degrees in Electrical Engineering & Computer Science and in Mathematics from the Massachusetts Institute of Technology (MIT). He earned a Master of Advanced Study degree in Mathematics (Part III of the Mathematical Tripos) with distinction from the University of Cambridge and holds a PhD in Electrical Engineering from Stanford University. Prior to his doctoral studies, Professor Moallemi developed quantitative methods in a number of entrepreneurial ventures as a partner in a $200 million fixed-income arbitrage hedge fund and as the director of scientific computing at an early-stage drug discovery start-up. He holds editorial positions at the journals Operations Research and Management Science. His research interests are in the area of the optimization and control of large-scale stochastic systems and decision-making under uncertainty with an emphasis on applications in financial engineering.

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