Companies like Google, Amazon, Microsoft, and Facebook have led the way in developing data-driven applications that have transformed our everyday lives. Based on the success of these data-driven pioneers, business leaders across all industries now realize the need to more effectively harness their own data to improve business operations and decision making. Managers who can effectively transform raw data into actionable insights, will not only predict the future but control it.
This course provides students the opportunity to learn business analytics and data science by working on a set of company sponsored applied projects. Students teams of 5-6 people, with 3-4 MBA students and 1-2 engineering (SEAs) students, will work hand in hand with the instructors and company representatives to achieve company goals through the practical application of data analytics. For example, students may be tasked with translating an e-commerce company’s website activity into a data-driven marketing campaign or building a tool to predict which of a SaaS company’s accounts are most likely to churn. The list of sponsoring companies spans large firms from financial services, cosmetics, media, and smaller NYC startups. Companies provide the data, faculty provides guidance on best practices, and your team will provide the answers.
Throughout this course, students execute on a data-driven project to:
o Use tools and idea from Business Analytics and Python’s analysis environment to solve interesting and exciting business problems
o Learn how to formulate relevant business questions that can be answered using data
o Understand the various steps of data preparation like data cleaning and feature extraction
o Break down a complex data problem into multiple smaller, solvable problems
o Evaluate the effectiveness of a solution through statistical testing
o Learn how to iterate on a solution to continually improve it
o Learn how to measure improvement using Key Performance Indicators (KPIs)
o Learn how to collaborate meaningfully with multiple stakeholders
o Communicate results to both technical and non-technical audiences
Example Company Projects (Subject to Change)
Ecommerce/Telemedicine: Work with a fast growing ecommerce company to better understand the connection between onsite user behavior and purchasing decisions. When are users willing to spend more? How long are users using the product? Can we predict when a customer needs new product (to preemptively market to them and capture spend)? Can we predict reorders? Can we build a model for who will reorder and why (and why not so that we can proactively drive retention)?
Financial Services: Work with a large bank to look at "people like you" and compare their income and spending patterns to yours...but instead of simply looking at current similar or "baseline" users, focus on consumers who were like you 3 years ago, but now are better off. What did they change to improve their state? Did they spend less, or spend more but increase their income? Did they take on debt (i.e., make payments to mortgage or debt companies) or did they change their location? This project aims to create an approach that would illustrate how "people like you" achieved some measure of financial success, by looking at their financial data.
SaaS/Artificial Intelligence: Work with a fast growing SaaS company to implement a predictive analytics solution to minimize customer service costs. Identify and automate redundant workflows using data driven algorithms. Build mechanisms to efficiently escalate service requests to humans when automated solutions are deemed likely to fail.
Retail/Data Analytics: Work with a large data provider to identify early indicators of retail closures. Identify and illustrate the potential for weather, location, and demographic trends to predict retail headwinds.
Adjunct Assistant Professor of Business
Brett Martin is co-Founder and Managing Partner of Charge Ventures, a pre-seed focused venture fund based in Brooklyn, NY. He also serves as an Adjunct Professor at Columbia Business School.
A 2x founder and 3x investor, Brett has spent his entire career building or investing in technology startups, including stints as an EIR @PrimaryVC (NYC-based seed stage fund with >$100MM AUM...