In recent years, the expectations for business students have shifted from mastering spreadsheets to developing skills in data science. The volume of information available to companies now includes web traffic, customer preferences, supply chain metrics, and social media sentiment. Understanding and interpreting this data requires more advanced tools and a new way of thinking.
Professor Vishal Lala, PhD, who teaches quantitative courses in marketing at the Lubin School of Business, commented on these changes: “Today’s businesses, armed with more data than ever before, are eager to unlock the power of data. They are looking for executives that have a sound understanding of business, have the ability to write computer code to analyze data, possess the statistical know-how to interpret it, and the acumen to effectively communicate results to senior management. They are looking for a Data Scientist who understands Business.”
While spreadsheets can explain past events in a business context, data science techniques such as predictive modeling and machine learning allow organizations to forecast trends and make decisions based on evidence rather than speculation.
Employers increasingly seek candidates who combine leadership with analytical abilities. Even a basic knowledge of data science can help job applicants stand out in fields like consulting, finance, or marketing.
Data science is not limited to coding or algorithm development; it involves using technical knowledge to inform better decisions. Algorithms reveal complex patterns within large datasets that might otherwise go unnoticed. The main benefit comes from applying these insights effectively in real-world scenarios.
For students preparing for careers in business, learning about data science is seen as essential preparation for an environment where leaders are expected to understand and use data in their decision-making processes.
