Concentration & Academics
Business Analytics Co-Concentration Classes of 2021-2023
Business Analytics draws upon a portfolio of methods and tools including statistics, forecasting, experimental design, data mining, and modeling to turn data into information and insights.
The Business Analytics co-concentration is designed to be a second concentration for Carroll School of Management students, who must choose a primary concentration such as Marketing, Information Systems, Operations Management, Management & Leadership, Accounting, or Finance.
The objectives of the undergraduate co-concentration are to develop managers who:
- possess a broad and deep understanding of theories and concepts in business analytics
- are adept at data management and analysis
- understand and utilize quantitative techniques for historical analysis, predictive analysis, modeling, and simulation
- are capable of applying analytical skills and knowledge to address management problems across disciplines and industries
The growing analytics field includes descriptive, predictive, and prescriptive analytics:
- Descriptive analytics helps organizations describe what has happened in their operating environment and includes gathering, organizing, tabulating, and communicating historical information: for example, how many online subscribers do we have?
- Predictive analytics helps organizations understand what to do by uncovering relationships and associations in the available data, and uses techniques such as probability and forecasting to reveal the likelihood of outcomes: for example, does the number of online subscribers increase when we have banner advertising on search sites?
- Prescriptive analytics is focused on understanding the causal effects that can be discerned from data sets, and strives to predict what will happen, given a particular course of action: for example, if we increase our banner advertising and provide one-click subscribing, how will the number of subscribers change?
To declare the Business Analytics co-concentration, see the form on the Undergraduate Advising page.
Courses for the Business Analytics co-concentration may be taken in any order, as long as prerequisites for individual classes are met. Up to one class from the co-concentration course list can be counted towards another concentration.
Courses
The following three courses are required for the co-concentration:
- ISYS3340 Data Analytics in Practice (fall, spring: formerly ISYS 6640 Analytics and Business Intelligence)
- BZAN6604 Management Science (fall, spring)
- BZAN3384 Predictive Analytics (fall, spring)
Select two additional courses:
- BZAN2021 Coding for Business (fall, spring) (or CSCI 1101)
- BZAN3304/BZAN6614 Quality Management (fall)
- BZAN3307 Machine Learning for Business Intelligence (fall, spring)
- BZAN3310 Sports Analytics (fall)
- BZAN3385 Applied Statistical Modeling (spring)
- BZAN6605 Risk Analysis & Simulation (spring)
- BZAN6606/MFIN6606 Forecasting Techniques (fall, spring, online)
- BZAN6608 Pricing & Revenue Optimization (fall)
- ISYS3257 Database Systems & Applications (fall, spring)
- ISYS3360 Machine Learning and Artificial Intelligence (fall)
- ISYS6621 Social Media and Digital Business (fall, spring)
- ISYS6645 Data Visualization (fall, spring)
- ISYS6625 Geographic Info Systems (fall, spring)
- MKTG2153 Customer Research and Marketing Decisions (fall, spring)
- MKTG 3114 Pricing and Demand Analytics (offered periodically)
- MKTG3161 Customer Relationship Management (offered periodically in fall, spring)
- MKTG3258 Advanced Marketing Analysis (offered periodically in fall, spring)
- ACCT6640 Dive, Dissect, and Decide with Big Business Data (spring)
- MFIN2270 Data Analytics in Finance (fall)
For questions about the Business Analytics co-concentration, please contact Stephanie Jernigan.
Additional Resources
Please view our additional resources below for more information about the skills you'll gain from pursuing this concentration, careers in business analytics, or to access additional training materials.
Students are strongly encouraged to take additional courses from the above list.
Business analytics is a collection of tools and techniques to turn data into insights for business decision making.
Analytics Magazine regularly features applications of analytics. The BC library has a subscription, so you can access it through that website (search for “analytics journal”) if you have difficulty browsing it directly.
The most important skill to have is an aptitude for problem solving. Some skills that are nice to have are familiarities with are:
- Programming (Python is the most commonly used general-purpose language and it is free.)
- Statistical software (R is the most widely used statistical software. It’s free, and the interface R Studio, also free, can make getting started a little easier.)
- Visualization software (Both Python and R have great visualization capabilities; Tableau is a standalone product that you can get a free student license for, and you’ll find that you can teach yourself a lot.)
- Getting data from databases.
Analytics has a wide range of applications. The tools you learn in the Business Analytics co-concentration apply not only to traditional business problems but to any issue of interest where data is collected. Below are a few examples.
Social impact
Marketing
- “How to Make the Most of Predictive Analytics,” Marketing Week.
- “Analytics Applications in Consumer Credit and Retail Marketing," Analytics. This one has lots of jargon and is a dense read, but also has lots of details about applications.
Healthcare
Investment Banking
- “How to Secure a Big Data Job in Investment Banking,” Efinancialcareers.
- “What is it Like to be a Data Scientist at an Investment Bank,” Quora.
Accounting
- “Business Analytics: Transforming the Role of Management Accountants,” Managing Accounting Quarterly (2015). Page 5 of this link has examples of how analytics is used in accounting.
There are lots of competitions and hackathons for students to practice their analytics skills, and experience with these can help to build students' resumes.
- ASA Data Fest
- Kaggle has a revolving menu of competitions.
Found a good resource that should be listed here? Email Stephanie Jernigan.
Business Analytics Co-Concentration Class of 2024 and Beyond
Business Analytics draws upon a portfolio of methods and tools including statistics, forecasting, experimental design, data mining, and modeling to turn data into information and insights.
The Business Analytics co-concentration is designed to be a second concentration for Carroll School of Management students, who must choose a primary concentration such as Marketing, Information Systems, Operations Management, Management & Leadership, Accounting, or Finance.
The objectives of the undergraduate co-concentration are to develop managers who:
- possess a broad and deep understanding of theories and concepts in business analytics
- are adept at data management and analysis
- understand and utilize quantitative techniques for historical analysis, predictive analysis, modeling, and simulation
- are capable of applying analytical skills and knowledge to address management problems across disciplines and industries
The growing analytics field includes descriptive, predictive, and prescriptive analytics:
- Descriptive analytics helps organizations describe what has happened in their operating environment and includes gathering, organizing, tabulating, and communicating historical information: for example, how many online subscribers do we have?
- Predictive analytics helps organizations understand what to do by uncovering relationships and associations in the available data, and uses techniques such as probability and forecasting to reveal the likelihood of outcomes: for example, does the number of online subscribers increase when we have banner advertising on search sites?
- Prescriptive analytics is focused on understanding the causal effects that can be discerned from data sets, and strives to predict what will happen, given a particular course of action: for example, if we increase our banner advertising and provide one-click subscribing, how will the number of subscribers change?
To declare the Business Analytics co-concentration, see the form on the Undergraduate Advising page.
Courses
Courses for the Business Analytics co-concentration may be taken in any order, as long as prerequisites for individual classes are met. Up to one class from the co-concentration course list can be counted towards another concentration.
The following two courses are required for the co-concentration:
- ISYS3350 Data Management for Analytics and Applications
- BZAN3385 Applied Statistical Modeling (spring)
Students must choose one of the following courses:
- BZAN3307 Machine Learning for Business Intelligence (spring)
- ISYS3360 Machine Learning and Artificial Intelligence (fall)
Students must choose two electives from the list below, where each elective comes from a different area of focus (Modeling, Data, or Applications).
Modeling
- BZAN2235 Modeling for Business Analytics
- BZAN6604 Management Science
Data
- ISYS6645 Data Visualization
- ISYS2160 IOS/Swift Programming
Applications
- ACCT6640 Dive, Dissect and Decide with Big Business Data
- MFIN2270 Data Analytics in Finance
- BZAN3310 Sports Analytics
- ISYS6625 Geographic Info Systems
- MKTG2153 Customer Research and Marketing Decisions
For questions about the Business Analytics co-concentration, please contact Stephanie Jernigan.
Additional Resources
Please view our additional resources below for more information about the skills you'll gain from pursuing this concentration, careers in business analytics, or to access additional training materials.
Students are strongly encouraged to take additional courses from the above list.
Business analytics is a collection of tools and techniques to turn data into insights for business decision making.
Analytics Magazine regularly features applications of analytics. The BC library has a subscription, so you can access it through that website (search for “analytics journal”) if you have difficulty browsing it directly.
The most important skill to have is an aptitude for problem solving. Some skills that are nice to have are familiarities with are:
- Programming (Python is the most commonly used general-purpose language and it is free.)
- Statistical software (R is the most widely used statistical software. It’s free, and the interface R Studio, also free, can make getting started a little easier.)
- Visualization software (Both Python and R have great visualization capabilities; Tableau is a standalone product that you can get a free student license for, and you’ll find that you can teach yourself a lot.)
- Getting data from databases.
Analytics has a wide range of applications. The tools you learn in the Business Analytics co-concentration apply not only to traditional business problems but to any issue of interest where data is collected. Below are a few examples.
Social impact
Marketing
- “How to Make the Most of Predictive Analytics,” Marketing Week.
- “Analytics Applications in Consumer Credit and Retail Marketing," Analytics. This one has lots of jargon and is a dense read, but also has lots of details about applications.
Healthcare
Investment Banking
- “How to Secure a Big Data Job in Investment Banking,” Efinancialcareers.
- “What is it Like to be a Data Scientist at an Investment Bank,” Quora.
Accounting
- “Business Analytics: Transforming the Role of Management Accountants,” Managing Accounting Quarterly (2015). Page 5 of this link has examples of how analytics is used in accounting.
There are lots of competitions and hackathons for students to practice their analytics skills, and experience with these can help to build students' resumes.
- ASA Data Fest
- Kaggle has a revolving menu of competitions.
Found a good resource that should be listed here? Email Stephanie Jernigan.
The Operations Management concentration provides students with knowledge of current issues in the Operations Management discipline. Intense competition in fast-paced global environments makes competencies in this field critical in both service and goods-producing organizations. This concentration is applicable to many industries and organizations, combining knowledge in business analytics, process design and analysis methods, project management, and operations management issues. The curriculum recognizes environmental, ethical, and social issues. The pedagogy entails lectures and discussions, case studies, field studies, and analytical modeling.
The objectives of the undergraduate concentration are to develop managers who:
- possess a broad and deep understanding of theories and concepts in Operations Management
- are capable of applying skills and knowledge to address management problems
- understand and utilize quantitative and qualitative analysis in decision making
- appreciate the role of operations in an organization and the interrelationships among functional areas
The Operations Management concentration builds upon the Carroll School of Management core, particularly complementing courses in statistics, organizational management, and economics. Our courses emphasize analysis and decision making and are explicitly designed to deliver the skills and knowledge required to successfully manage people, processes, and systems in today's competitive environment.
The concentration is designed to intersect with other functional disciplines, making Operations Management an excellent complement to other concentrations including Accounting, Business Analytics, Finance, Marketing, Information Systems, or Management & Leadership.
The following two courses are required for the concentration:
- BZAN3375 Operations Strategy and Consulting (fall)
- BZAN2255 Managing Projects (spring)
Also required are two of the following courses:
- BZAN3304/BZAN6614 Quality Management (fall)
- BZAN3310 Sports Analytics (fall)
- BZAN3332 Supply Chain Management (spring)
- BZAN3384 Predictive Analytics (fall/spring)
- BZAN6604 Management Science (fall/spring)
- BZAN6605 Risk Analysis & Simulation (spring)
- BZAN6606 Forecasting Techniques (fall/spring/online)
- BZAN6608 Pricing & Revenue Optimization (fall)
Students are strongly encouraged to take additional courses from the above list.
To declare the Operations Management concentration, see the form on the Undergraduate Advising page.
Although there are no particular prerequisites needed in order to qualify for study abroad, the usual course prerequisites still apply. There is no limit to how many courses taken abroad will be allowed for major credit. If the courses are judged equivalent and if the proposed courses constitute a reasonable selection, major or elective credit will be given. After acceptance into a study abroad program the student should then see the department chair for course approvals before going abroad. Students must provide a copy of the syllabus and course description for approval.