Reflecting on my time in Duke’s Master of Quantitative Management: Business Analytics program, I vividly remember a moment during my work when the perfect alignment of my education with real-world challenges became starkly clear. As I sat in a client meeting at Walmart Data Ventures, tasked with finding a way to help our suppliers understand sales trends better, I realized that everything I had learned at MQM was about to be put to the test.

My product manager role at Walmart Data Ventures involves turning vast amounts of data into accessible, actionable insights capabilities for our suppliers — helping them make informed decisions that ultimately benefit customers. It’s challenging, and the MQM program has set me up for success in this dynamic environment by emphasizing a balanced curriculum of technical skills, industry knowledge, and soft skills.

Building Technical Skills

One of the fundamental courses that have had a lasting impact was Programming for Data Analytics. These programming capabilities allow me to understand and manipulate data efficiently, ensuring that insights are not only accurate but also actionable. Additionally, the Data Infrastructure course equipped me with essential knowledge about data storage, cleansing, and retrieval using SQL, which is vital for maintaining the integrity and availability of data in the product.

Becoming an Excellent Communicator and Critical Thinker

But it wasn’t all about technical skills. Courses like Critical Thinking and Collaboration, Business Communication, and Navigating Organizations have come into play every day as I navigate user issues, distill product requirements, and align the initiatives with broader business strategies to deliver solid ROI. For example, when faced with conflicting needs on a new product feature, I used the negotiation and persuasion skills I developed at MQM to align all stakeholders around a unified vision, ensuring the project moved forward smoothly.

A photo taken from a desk in a classroom at Duke University's Fuqua School of Business. In the foreground, there is a nametag that reads "Dora Zhao, Class of 2022"

Navigating Ethical Questions and Tough Decisions

On the decision-making front, the Decision Analytics and Modeling course equipped me with tools to tackle uncertainty — through decision trees, Monte Carlo simulations, and optimization techniques. These are incredibly useful when I must make tough calls on product features or go-to-market strategies.

Moreover, the exposure to data science and modern analytics has been critical. The Data Science for Business and Modern Analytics: Data, Predictions, Actions courses not only covered advanced analytical techniques like machine learning and natural language processing (NLP) but also emphasized the ethical considerations of deploying such technologies. This holistic understanding is crucial when I give feedback on designs or develop go-to-market strategies that align with ethical standards and business goals.

Assessing Risk in Product Management

Additionally, the Fraud Analytics and Managing Cybersecurity Risk courses resonate with my role as they align with modern business’s emphasis on security and integrity in managing vast amounts of consumer data. These classes provided a deep dive into detecting and preventing fraudulent behavior and understanding cybersecurity, which are increasingly important in today’s digital age.

In a nutshell, the MQM program has not only provided me with a powerful toolkit of technical skills but has also polished my soft skills, enabling me to bridge the gap between data and strategic decision-making effectively. Every day, I use what I learned at MQM to ensure the data product I’m building meets our stakeholders’ needs and helps suppliers better serve customers.

Looking ahead, I see the skills and knowledge from the MQM program as vital tools I will continue to rely on to meet future challenges. This journey of learning and applying has just begun, and I am excited to continue making a significant impact in the field of data-driven decision-making.