Business intelligence is the application of systems thinking, data mining, pattern recognition, mathematical modeling, statistics, computing, and simulation to solve challenging business problems. This young discipline, also called business analytics or systems analytics, began in the mid-1990s when powerful desktop computers, computer-network communications services, massive data storage options, and advanced data mining and data visualization software tools all became available.
Many large companies have created business intelligence work groups. Dow Chemical Company, Ford Motor Company, General Motors, and Proctor & Gamble are leading manufacturers with successful pioneering business intelligence efforts. This approach has proven effective in many aspects of these corporations: strategic planning, systems engineering, marketing, sales and order fulfillment, risk analysis, purchasing, warranty management, technology and capabilities analysis, supply chain management, etc. These areas greatly expand traditional mathematical efforts in computer-aided engineering. The banking and insurance industries successfully apply business intelligence to investment portfolio and credit risk analysis. Wal-Mart is a leading user among retailers of business intelligence. The health services delivery sector has begun to apply this approach to its vast and complex data.
Business intelligence projects typically involve the integration of data from internal and external sources. Data types include numeric, text, geographic, and image data. Biotechnology analytics has genomic data at its center. Data volumes are often so large that manual analysis is impossible. “Artificial intelligence” methods enable researchers to cluster data and explore for patterns. Specialists in business intelligence create mathematical models and simulations to represent problems, study business alternatives and scenarios, and generate forecasts. Successful projects provide management with insights and better decision-making tools, based on current data. These increase management awareness of business performance and dynamics and clarify competitive pressures and growth opportunities.
The new efforts in business intelligence are a significant contribution to American competitiveness in the global economy. Masters-educated graduates with appropriate preparation are ready to contribute to this growing field and are likely to become its staffing backbone. The approximately 20 mathematics-centered professional science master’s degree programs available today in such fields as industrial mathematics, financial mathematics, bioinformatics, and mathematical entrepreneurship are outstanding training grounds for a career in business intelligence, as the employment opportunities afforded to their graduates testify.