Information Technology and Analytics MS

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Information Technology and Analytics: Online
Master of science degree

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Online Admissions Contact

Karen Palmer, Associate Director Combined Accelerated Programs
585-475-5656,

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Offered within the
School of Information

A degree driven by real-time employer demand

These jobs are growing by 12%, more than double the rate of the overall labor market.

The information technology and analytics job market

14%

Database administrator job growth

1M+

Job listings with SQL skills

91K+

Average salary nationwide

82%

Demand growth for data analysis in this field

Program Highlights

Demand for information technologists, data scientists, and data-driven decision-makers across all fields now comprise one-third of the data-savvy professional job market. The MS degree in Information Technology and analytics addresses this demand at the intersection of Information Technology and Data Science. With a program rich in analytics and in-depth, career-oriented study, you will explore how information is organized, verified, analyzed, and applied in today's data-rich environment.

This degree shares curriculum with the data science master's degree, and is of particular value to professionals in the field of Information Technology who need to upskill in data science knowledge to handle the huge volumes of data organizations must utilize. In this degree, you will apply critical, analytical thinking to database design, management, and mining. The program culminates with a capstone course where you will demonstrate competency for the theory and application of information technology and data analytics.

Curriculum packed with high-demand skills

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Data Analytics

Demand for data analytics skills are growing 82%, and expertise in big data carries a salary premium.

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Data Visualization

Demand for Tableau skills are growing 87%.

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Software and Programming

Demand for these skills is growing 61%.

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SQL

Nearly half of all postings for jobs in this field require advanced SQL skills.

Curriculum

ISTE-600
Foundations of Data Mining
Credits 3
This course provides students with exposure to foundational data mining techniques. Topics include analytical thinking techniques and methods, data/exploring data, classification algorithms, association rule mining, cluster analysis and anomaly detection. Students will work individually and in groups on assignments and case study analyses.
ISTE-605
Scholarship In Information Technology And Analytics
Credits 3
ITA graduate students are expected to make a scholarly contribution as a requirement for the MS degree. The Scholarship in Information Technology and Analytics course provides students with the fundamental skills needed to define and conduct a program of scholarly investigation in the form of a capstone or thesis project. The course focuses on skills such as academic writing, searching the literature, identifying and articulating interesting and important topics and problems, scholarship ethics, developing capstone proposals, critical thinking, and effective oral and written communication and presentation of scholarship.
ISTE-610
Non-Relational Data Management
Credits 3
This course provides students with exposure to foundational information sciences and technologies. Topics include an overview of data types, structuring and processing data and knowledge, data transformation, and data storage and warehousing. Students will work with non-traditional (noSQL) data stores to manage large datasets in the context of specific problem scenarios.
ISTE-612
Information Retrieval and Text Mining
Credits 3
This is the second course in a two-course sequence that provides students with exposure to foundational information sciences and technologies. Topics include internet middleware technologies, data and text analytics, and information visualization. Note: One year of programming in an object-oriented language, a database theory course, a course in Web development, and a statistics course is needed.
ISTE-721
Information Assurance Fundamentals
Credits 3
This course provides an introduction to the topic of information assurance as it pertains to an awareness of the risks inherent in protecting digital content in today’s networked computing environments. Topics in secure data and information access will be explored from the perspectives of software development, software implementation, data storage, and system administration and network communications. The application of computing technologies, procedures and policies and the activities necessary to detect, document, and counter unauthorized data and system access will be explored. Effective implementation will be discussed and include topics from other fields such as management science, security engineering and criminology. A broad understanding of this subject is important for computing students who are involved in the architecting and creation of information and will include current software exploitation issues and techniques for information assurance.
ISTE-724
Data Warehousing
Credits 3
This course covers the purpose, scope, capabilities, and processes used in data warehousing technologies for the management and analysis of data. Students will be introduced to the theory of data warehousing, dimensional data modeling, the extract/transform/load process, warehouse implementation, dimensional data analysis, and summary data management. The basics of data mining and importance of data security will also be discussed. Hands-on exercises include implementing a data warehouse.
ISTE-780
Data Driven Knowledge Discovery
Credits 3
Rapidly expanding collections of data from all areas of society are becoming available in digital form. Computer-based methods are available to facilitate discovering new information and knowledge that is embedded in these collections of data. This course provides students with an introduction to the use of these data analytic methods, with a focus on statistical learning models, within the context of the data-driven knowledge discovery process. Topics include motivations for data-driven discovery, sources of discoverable knowledge (e.g., data, text, the web, maps), data selection and retrieval, data transformation, computer-based methods for data-driven discovery, and interpretation of results. Emphasis is placed on the application of knowledge discovery methods to specific domains.
ISTE-782
Visual Analytics
Credits 3
This course introduces students to Visual Analytics, or the science of analytical reasoning facilitated by interactive visual interfaces. Course lectures, reading assignments, and practical lab experiences will cover a mix of theoretical and technical Visual Analytics topics. Topics include analytical reasoning, human cognition and perception of visual information, visual representation and interaction technologies, data representation and transformation, production, presentation, and dissemination of analytic process results, and Visual Analytic case studies and applications. Furthermore, students will learn relevant Visual Analytics research trends such as Space, Time, and Multivariate Analytics and Extreme Scale Visual Analytics.
ISTE-740
Geographic Information Science And Technology
Credits 3
This course provides a survey of the theory, concepts, and technologies related to representation and understanding of the earth - a scientific domain known as Geographic Information Science and Technology (GIS & T). Students will gain hands-on experience with technologies such as Global Positioning Systems (GPSs), Geographic Information Systems (GISs), remote sensing, Virtual Globes (Google Earth), and web mapping mashups. Furthermore, students will learn relevant GIS & T theory, concepts, and research trends such as spatial reasoning, spatiotemporal data representation, and spatial analysis.
ISTE-795
Capstone In Information Sciences And Technologies
Credits 3
This is the project-based capstone course for the master of science in information sciences and technologies program. Students work in teams to complete a substantial, integrative large scale system development projects. Submission of a project proposal, a formal set of development artifacts, a final project report, and a public defense with system demonstration are required.

Admission Requirements

  • Hold a baccalaureate degree (or equivalent) from an accredited institution (3.00 GPA strongly recommended).
  • Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
  • Submit a current resume or curriculum vitae.
  • Submit two letters of recommendation from academic or professional sources.
  • A background in information technology concepts including object-oriented. programming, website development, database theory and practice, and statistics is expected
  • A test of English Language aptitude (TOEFL) is required of all applicants and course registrants whose native language is not English. Applicants are exempt from submitting exams if they have worked or studied in the U.S. for the last two years or they are from countries and attended universities whose native language is English.
  • Applicants from foreign universities must submit GRE scores. Scores from the GRE are strongly recommended for applicants whose undergraduate grade point average is less than 3.0.

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