Online Master of Science in Computer Information Systems Concentration in Data Analytics

The MS in Computer Information Systems (MSCIS) concentration in Data Analytics will provide professionals with the skills required to compete for jobs as data scientists, analysts, architects, and engineers amid rising global demand. The concentration will explore the intricacies of data analytics and expose students to various topics related to data processing, analysis, and visualization. Along with probability theory and statistical analysis methods and tools, students will learn how to generate relevant visual presentations of data and will examine and concepts and techniques for data mining, text mining, and web mining. In addition to the broad background in the theory of practice of information technology gained from the Computer Information Systems core courses, individuals who complete this program will have a solid knowledge of data analytics practices accompanied by exposure to the methods and tools for data mining and knowledge discovery.

Students who complete the MSCIS degree concentration in Data Analytics will be able to demonstrate:

  • Familiarity with applied probability and statistics, and their relevance in day-to-day data analysis.
  • The ability to explore the various data visualization techniques and their applications using real-world data sets.
  • An understanding of web analytics and metrics; how to procure and process unstructured text; and hidden patterns.
  • Skills in facilitating knowledge discovery using data mining techniques over vast amounts of data.

Why Choose BU’s Master of Science in Computer Information Systems?

  • U.S. News & World Report Best Online Programs in Grad Computer Information Technology 2017In 2017, the MSCIS ranked #4 among the Best Online Graduate Computer Information Technology Programs (U.S. News & World Report).
  • Students benefit from a supportive online network, with courses developed and taught by PhD-level full-time faculty and professionals with hands-on expertise in the industry.
  • Small course sections ensure that students get the attention they need, while case studies and real-world projects ensure that they gain in-depth, practical experience with the latest technologies.

Meet Dr. Suresh Kalathur, one of the faculty members you’ll work with in the Computer Information Systems program.

Career Outlook

Computer and Information Systems Managers

15% increase in jobs through 2024

$131,600 median annual pay in 2015

Computer and Information Research Scientists

11% increase in jobs through 2024

$110,620 median annual pay in 2015

Computer Systems Analysts

21% increase in jobs through 2024

$85,800 median annual pay in 2015

Database Administrators

11% increase in jobs through 2024

$81,710 median annual pay in 2015

Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2016-17 Edition

Best Technology Jobs, 2016 U.S. News & World Report

  • #1 Computer Systems Analyst
  • #2 Software Developer
  • #3 Web Developer
  • #4 IT Manager
  • #5 Information Security Analyst
  • #6 Database Administrator
  • #8 Computer Systems Administrator

By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.

McKinsey & Company Big data: The Next Frontier for Innovation, Competition, and Productivity, 2011

Tuition & Financial Assistance

Money Matters

Boston University Metropolitan College (MET) offers competitive tuition rates that meet the needs of part-time students seeking an affordable education. These rates are substantially lower than those of the traditional, full-time residential programs yet provide access to the same high-quality BU education. To learn more about current tuition rates, visit the MET website.

Financial Assistance

Comprehensive financial assistance services are available at MET, including graduate assistantships (up to $4,200 per semester), scholarships, graduate loans, and payment plans. There is no cost to apply for financial assistance, and you may qualify for a student loan regardless of your income. Learn more.

Curriculum

The online Master of Science in Computer Information Systems consists of ten courses (40 credits).

Students pursuing the concentration in Data Analytics must complete the following courses:

MSCIS Core Courses

(Five courses/20 credits)

METCS625 Business Data Communication and Networks

This course presents the foundations of data communications and takes a bottom-up approach to computer networks. The course concludes with an overview of basic network security and management concepts. Prereq: MET CS 200, or instructor's consent. This course may not be taken in conjunction with MET CS 425 (undergraduate) or MET CS 535. Only one of these courses can be counted towards degree requirements. [4 credits]

METCS669 Database Design and Implementation for Business

Students learn the latest relational and object-relational tools and techniques for persistent data and object modeling and management. Students gain extensive hands- on experience using Oracle or Microsoft SQL Server as they learn the Structured Query Language (SQL) and design and implement databases. Students design and implement a database system as a term project. Restrictions: Only for MS CIS. This course may not be taken in conjunction with MET CS 469 (undergraduate) or MET CS 579. Only one of these courses can be counted towards degree requirements. [4 credits]

METCS682 Information Systems Analysis and Design

Object-oriented methods of information systems analysis and design for organizations with data- processing needs. System feasibility; requirements analysis; database utilization; Unified Modeling Language; software system architecture, design, and implementation, management; project control; and systems-level testing. [4 credits]

METCS782 IT Strategy and Management

This course describes and compares contemporary and emerging information technology and its management. Students learn how to identify information technologies of strategic value to their organizations and how to manage their implementation. The course highlights the application of I.T. to business needs. CS 782 is at the advanced Masters (700) level, and it assumes that students understand IT systems at the level of CS 682 Systems Analysis and Design. Students who haven't completed CS 682 should contact their instructor to determine if they are adequately prepared. Prereq: MET CS 682, or instructor's consent. [4 credits]

And one of the following*:

METCS520 Information Structures with Java

This course covers the concepts of object-oriented approach to software design and development using the Java programming language. It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, applets, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, interfaces, creating user interfaces, exceptions, and streams. Upon completion of this course the students will be able to apply software engineering criteria to design and implement Java applications that are secure, robust, and scalable. Prereq: MET CS 200 or MET CS 300 or Instructor's Consent. Not recommended for students without a programming background. [4 credits]

METCS521 Information Structures with Python

This course covers the concepts of the object-oriented approach to software design and development using the Python programming language. It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, creating user interfaces, exceptions and streams. Upon completion of this course students will be capable of applying software engineering principles to design and implement Python applications that can be used in conjunction with analytics and big data. Prerequisite: MET CS 200 Fundamentals of Information Technology or MET CS 300 Foundations of Modern Computing or instructor's Consent. Not recommended for students without a programming background. [4 credits]

*If a student chooses to take both MET CS 520 and MET CS 521, the first course completed will fulfill the core requirement and the second course completed will count as an elective.

Students who have completed courses on core curriculum subjects as part of their undergraduate degree program or have relevant work-related experience may request permission from the Department of Computer Science to replace the corresponding core courses with graduate-level computer information systems electives. Please refer to the MET CS Academic Policies Manual for further details.

Concentration Requirements

(Five courses/20 credits)

METCS544 Foundations of Analytics

The goal of this course is to provide students with the mathematical and practical background required in the field of data analytics. Starting with an introduction to probability and statistics, the R tool is introduced for statistical computing and graphics. Different types of data are investigated along with data summarization techniques and plotting. Data populations using discrete, continuous, and multivariate distributions are explored. Errors during measurements and computations are analyzed in the course. Confidence intervals and hypothesis testing topics are also examined. The concepts covered in the course are demonstrated using R. Laboratory Course. Prereq: MET CS 546 or equivalent knowledge, or instructor's consent. [4 credits]

METCS546 Quantitative Methods for Information Systems

The goal of this course is to provide Computer Information Systems students with the mathematical fundamentals required for successful quantitative analysis of problems in the field of business computing. The first part of the course introduces the mathematical prerequisites for understanding probability and statistics. Topics include combinatorial mathematics, functions, and the fundamentals of differentiation and integration. The second part of the course concentrates on the study of elementary probability theory, discrete and continuous distributions. Prereq: Academic background that includes the material covered in a standard course on college algebra or instructor's consent. [4 credits]

METCS555 Data Analysis and Visualization

This course provides an overview of the statistical tools most commonly used to process, analyze, and visualize data. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis. These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results, are discussed. Concepts are presented in context of real world examples. Recommended Prerequisite: MET CS 544 or equivalent knowledge, or instructor's consent. [4 credits]

METCS688 Web Analytics and Mining

The Web Analytics and Mining course covers the areas of web analytics, text mining, web mining, and practical application domains. The web analytics part of the course studies the metrics of web sites, their content, user behavior, and reporting. Google analytics tool is used for collection of web site data and doing the analysis. The text mining module covers the analysis of text including content extraction, string matching, clustering, classification, and recommendation systems. The web mining module studies how web crawlers process and index the content of web sites, how search works, and how results are ranked. Application areas mining the social web and game metrics will be extensively investigated. Laboratory Course. Prerequisites: MET CS 544, or MET CS 555 or equivalent knowledge, or instructor's consent. [4 credits]

METCS699 Data Mining

The goal of this course is to study basic concepts and techniques of data mining. The topics include data preparation, classification, performance evaluation, association rule mining, and clustering. We will discuss basic data mining algorithms in the class and students will practice data mining techniques using data mining software. Students will use Weka and SQL Server or Oracle. Prereq: MS CS Prerequisites: MET CS 579; or instructor's consent. MS CIS Prerequisites: MET CS 669 and MET CS 546; or instructor's consent. [4 credits]

Applicants to the program are required to have a bachelor’s degree from a regionally accredited institution and proficiency equivalent to the following areas:

METCS200 Fundamentals of Information Technology

This course is a technically-oriented introductory survey of information technology. Students learn about basic computer information, different types of business systems and basic systems analysis, design and development. Students also study basic mathematics, software development and create simple Java programs. [4 credits]

If college-level credit courses are not in evidence, the department will determine what prerequisite courses must be completed in addition to graduate degree requirements. Students claiming equivalent proficiency in the prerequisite courses from non-academic sources must take an examination to demonstrate such proficiency.

Faculty

Eric Braude

Eric Braude

Associate Professor of Computer Science
PhD, Columbia University; MS, University of Miami; MS, University of Illinois; BS, University of Natal (South Africa) 

Areas of Specialization: Software Engineering with Object-Oriented Methods; Software Design

Lou Chitkushev

Lou Chitkushev

Associate Dean for Academic Affairs and Associate Professor of Computer Science; Director of Health Informatics and Health Sciences Programs
PhD, Boston University; MS, Medical College of Virginia; MS, BS, University of Belgrade

John Day

John Day

Lecturer in Computer Science
MSEE, BSEE, University of Illinois

Stu Jacobs

Stu Jacobs

Lecturer in Computer Science
MS, Southern Connecticut State University; BS, University of Wisconsin, Madison

Suresh Kalathur

Suresh Kalathur

Assistant Professor of Computer Science; Director of Analytics Programs
PhD, Brandeis University; MS, Indian Institute of Technology; BS, Regional Engineering College (Warangal, India) 

Vijay Kanabar

Vijay Kanabar, PMP

Associate Professor of Computer Science; Director of Project Management Programs
PhD, University of Manitoba (Canada); MS, Florida Institute of Technology; MBA, Webber College; BS, University of Madras (India) 

Jae Young Lee

Jae Young Lee

Assistant Professor of Computer Science
PhD, MS, University of Texas at Arlington; BS, Seoul National University (Korea)

Robert Schudy

Robert Schudy

Associate Professor of Computer Science
PhD, MS, University of Rochester; BA, University of California San Diego

Victor Shtern

Victor Shtern

Associate Professor Emeritus of Computer Science
PhD, Leningrad Aluminum Institute (Russia); MS, Leningrad Institute of Technology; MBA, Boston University 

Anatoly Temkin

Anatoly Temkin

Assistant Professor and Chair of Computer Science
PhD, Kazan University (Russia); MS, Moscow University 

Guanglan Zhang

Guanglan Zhang

Assistant Professor of Computer Science; Faculty Coordinator for Health Informatics Programs
PhD, MEng, Nanyang Technological University, Singapore; BS, Luoyang Institute of Technology

Yuting Zhang

Yuting Zhang

Assistant Professor of Computer Science
PhD, Boston University; MS, BS University of Science and Technology Beijing

Tanya Zlateva

Tanya Zlateva

Dean of Metropolitan College and Professor of the Practice of Computer Science and Education; Director of Security Programs
PhD, Dresden University of Technology (Germany); MS, Dresden University of Technology; BS, Dresden University of Technology

Getting Started

To learn more or to contact an enrollment advisor before you get started, request information using the button below and tell us a little about yourself. Someone will be in touch to answer any questions you may have about the program and detail the next steps in earning your degree. You can also start your application or register for a course at Metropolitan College.