Business Intelligence


M.S. IN COMPUTING


NEWS

NewsSee what's new for the Computing Program


FOLLOW US

Twitter: MUMSComp
LinkedIn: Marquette University MS in Computing

Businesses have progressed through the stages of developing data bases, information retrieval systems, reporting tools, and decision support. Business is demanding analysis of the current state and a look to the future to predict outcomes of alternate strategies.

A new flavor of career in information systems has developed that requires more understanding of the business, better partnerships, and increased analytic skills. Math modeling and computing resources are required to supply the answers. The connection of the Computing program to mathematics and statistics and the Graduate School of Management combine with the flexible curriculum of the program to provide the knowledge to succeed in this fertile career path. In addition to the courses listed below, the Graduate School of Management has courses for quantitative analysis of operations and supply chain, economics, marketing, and human resources.

Courses offered in the Business Analytics and Business Intelligence concentration:

Course Number Title Description

MSCS 5610 or MSCS 6330

Data Mining

Techniques for extracting patterns from large databases. Classification, prediction, clustering, summarization and discrimination.

MSCS 5800 or

MSCS 6380

Principles of Data Base Systems/
Advanced Database Systems

Database concepts and architecture. Data modeling, transaction, security Web access and distributed query.

MSCS 6010

Probability

Modeling random processes and Bayesian approaches, random variable distribution functions, expectation, discrete and continuous distributions, Bayesian paradigm.

MSCS 6020

Simulation

Statistical simulation and modeling, Monte Carlo, Markov, applications, validation, and analysis.

MSCS 6030

Applied Mathematical Analysis

Foundational topics in analysis, modeling, proof of approximations, solutions in applications.

MSCS 6040

Applied Linear Algebra

Foundational linear algebra, linear systems, eigenvalues and eigenvectors, transformation, problems arising in applications.

MSCS 6060 or

MSCS 6350

Parallel and Distributed Systems/
Distributed Computing

Software for parallel and distributed systems, tools, approaches, architecture, heterogeneity, and solving business problems.

MSCS 6370

Information Representation

Grammars and languages for communicating business information in diverse systems.

MSCS 6391

Topics MSCS: Text Mining

Deriving information from text, statistical pattern learning, interfaces to databases, categorization, clustering, concept extraction and summarization.

MSCS 6391

Topics MSCS: Data Warehouse

Use of databases, online analytical processing, ETL, data dictionaries and metadata to support business reporting.

MSCS 6391 Topics: Business Intelligence An introduction to the process, terminology, and most common data mining techniques. Features hand-on exercises with a variety of the techniques for data preparation, visualization, performance evaluation, prediction and classification, cluster analysis and association rules. Includes a discussion of best practices for application selection and delivery.
MSCS 6391 Topics: Business Analytics Study of several data mining techniques with hands-on experience using medium sized data sets. Investigation of techniques for data integration and exploration. Industry focused review of most beneficial applications of data mining.

INTE 6150

Information Technology Strategy

Information flow, governance, exploiting information to support the business.

    There are several courses in the Graduate School of Management that study analytical and quantitative modeling of business systems that are applicable to this concentration.

Note: Enrollment in the Graduate School of Management courses requires the consent of the MBA Director and the Computing program academic advisor.


SITE MENU

 

Summer 2013 Research Experience

The Department of Mathematics, Statistics and Computer Science hosted the NSF-funded Summer 2013 Research Experience (REU) for Undergraduates. This program provides U.S. undergraduates with an intensive, faculty-mentored, summer research experience in the areas of applied mathematics, high-performance computing, statistics, ubiquitous systems and mathematics education. Learn more