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Co-Concentration in Business Analytics

Business Analytics is the emergent capability for organizations in the twenty-first century. All organizations, regardless of industry, size, or operating environment generate and manage large volumes of data and information that, used well, inform the decision making and competitive capabilities of the enterprise. The emerging area of analytics is focused on using business data to examine what already happened, to determine or predict what will happen, and to explore or model what should happen. Successful managers across functional areas, whether finance, marketing, operations, human resources, or information systems, need to be able to understand and utilize business analytics in order to manage and lead effectively.

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 field includes descriptive, predictive, and prescriptive analytics. Descriptive analytics help organizations describe what has happened in their operating environment and includes gathering, organizing, tabulating, and communicating historical information, e.g., 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, the number of online subscribers increases 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?

The Business Analytics co-concentration builds upon the Carroll School of Management core. The co-concentration is designed to align with a variety of functional disciplines making Business Analytics an excellent complement to other concentrations including Accounting, Operations Management, Finance, Marketing, Information Systems, or Management and Leadership.

Objectives of the Undergraduate Co-Concentration in Business Analytics

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

Careers in Business Analytics

Rather than simply answering questions about what, how, when, and where things have happened, today’s business analysts are able to push the use of data further, find out why things are happening and what will happen if identified trends continue, and model how an organization can use this information to optimize outcomes. Careers that utilize the skills and knowledge of business analytics continue to emerge and grow in all fields and business disciplines. Students with this co-concentration may pursue careers in consulting, financial services, healthcare services, accountancy, technology management, government, manufacturing, and not-for-profit organizations. The demand for managers with these skills is strong and will increase as firms continue to recognize that they compete not only with new products and services, but also with a high degree of competence in managing their data, information, and business intelligence.

Business Analytics Co-Concentration Requirements

Business Analytics Co-Concentration Class of 2023

The following three courses are required for students co-concentrating in Business Analytics who belong to the class of 2023:

  • ISYS3340 Data Analytics in Practice (fall and spring)
  • BZAN3384 Predictive Analytics (fall and spring)
  • BZAN6604 Management Science (fall and spring)

Select two additional courses, excluding any courses taken from above list:

  • BZAN3304/BZAN6614 Quality Management (fall)
  • BZAN3307 Machine Learning for Business Intelligence (fall and spring)
  • BZAN3310 Sports Analytics (fall and spring)
  • BZAN3385 Advanced Statistical Modeling (spring)
  • BZAN6605 Risk Analysis and Simulation (offered periodically)
  • BZAN6606/MFIN6606 Forecasting Techniques (fall, online, and spring)
  • BZAN6608 Pricing and Revenue Optimization (offered periodically)
  • ISYS2157 Programming for Management and Analytics (fall and spring) (or CSCI1101)
  • ISYS3257 Database Systems and Applications (fall and spring)
  • ISYS3360 Machine Learning and Artificial Intelligence (fall)
  • ISYS6621 Social Media, Emerging Technologies, and Digital Business (fall)
  • ISYS6625 Geographic Information Systems (fall and spring)
  • ISYS6645 Data Visualization (fall and spring)
  • MKTG2153 Customer Research and Insights for Marketing Decisions (fall and spring)
  • MKTG3114 Pricing and Demand Analytics (offered periodically)
  • MKTG3161 Customer Relationship Management (fall and spring)
  • MKTG3258 Marketing Analytics for Customer Insights (spring)
  • ACCT6640 Dive, Dissect, and Decide with Big Business Data (spring)
  • MFIN2270 Data Analytics in Finance (fall and spring)

Business Analytics Co-Concentration Classes of 2024 and Beyond

The following three courses are required for students co-concentrating in Business Analytics who belong to the class of 2024 and beyond:

  • ISYS3340 Data Analytics in Practice (fall, spring)
  • BZAN3385 Advanced 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
  • ISYS3257 Database Systems and Applications
  • 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 
Wed, 26 Aug 2020 04:39:00 -0500 en text/html https://www.bc.edu/bc-web/academics/sites/university-catalog/undergraduate/csom/business-analytics.html
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