| Call Number | 12462 |
|---|---|
| Day & Time Location |
M 4:10pm-6:00pm To be announced |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | John Nives |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | This elective course integrates analytic methodology with technology application to prepare students to lead data-informed decision-making in digital environments. Students learn how to convert digital signals into accountable, value-creating decisions, and move systematically from signal to insight to decision to value. This course emphasizes decision architecture, executive translation, and value creation in digital ecosystems. Students develop the ability to interpret digital signals, assess analytic maturity, evaluate methodological rigor, and design actionable analytics roadmaps aligned to organizational strategy and governance. The course combines conceptual frameworks, peer-reviewed research, hands-on demonstrations of leading digital analytics and AI tools, and applied exercises grounded in real organizational contexts. This 3-credit elective was developed for the M.S. in Technology Management (TMGT) program at Columbia University’s School of Professional Studies. The course supports the program’s mission to bridge theory and practice by equipping students with applied analytical frameworks grounded in research and industry practice, preparing them to lead digital transformation initiatives with strategic, ethical, and organizational awareness. Space permitting, the course is open to cross-registrants from other Columbia graduate programs whose academic or professional interests involve analytics-informed decision-making. No advanced programming or data engineering background is required; however, students are expected to have foundational business literacy and a strong interest in applying analytics to real-world organizational challenges. |
| Web Site | Vergil |
| Department | Technology Management |
| Enrollment | 0 students (30 max) as of 2:06PM Tuesday, March 31, 2026 |
| Subject | Technology Management |
| Number | PS5134 |
| Section | 001 |
| Division | School of Professional Studies |
| Open To | Professional Studies |
| Section key | 20263TMGT5134K001 |