BZAN7707 · Business Analytics
Carroll School of Management
Information Technology (IT) and Data Analytics now permeate the strategy, structure, and operations of modern enterprises, and new business practices have led to an orders of magnitude increase in the amount of data available for analysis and decision-making. It is essential that managers develop a deep understanding of how data can be structured, captured, and queried in order to support operations, decision-making, and strategic insight. At the same time, managers must become fluent with IT so that they can promote innovative strategic initiatives that are increasingly data and IT dependent. In this course, students will develop an understanding of IT theory and practice, study key emerging technologies, and develop their ability to identify new opportunities made possible by IT. This course will also provide students with a deep understanding of data and analytics by exploring how business processes are analyzed, data is modeled (using entity relationship diagrams), databases are designed, and data is queried using SQL. This combination of theory and practice will allow students to develop their ability to identify and take advantage of the new opportunities now made possible by data analytics and Information Technology. The on-campus section of this course (BZAN7707) will meet weekly on campus. Please note that the online asynchronous section of this course will also include two or three synchronous web conferences during the semester. Please review the course syllabus for the schedule for these web conferences, or contact the instructor. STEM-designated This course was formerly numbered: ISYS7700
Course experience
Averages use the original five-point historical evaluation scale.
Organization
4.2 / 5
How well the course was organized
Challenge
4.4 / 5
How intellectually challenging students found it
Attendance
4.2 / 5
How necessary attendance was
Assignments
4.2 / 5
How helpful assignments were
Weekly effort
~5
hours per week
Estimated from the original workload response buckets. Individual sections may differ.
Instructor options
Ratings below reflect only recovered evaluations connected to this course.
Across time
Section-level results available in the recovered archive.
Spring 2025
2 sectionsFall 2024
2 sections