Study Synchronously Online or On Campus: It's Your Choice
STEM-Certified Program
The Technology/Database concentration focuses on building skills to develop and use databases, including SQL, and to become proficient in modern programming languages such as Python and R. These skills are applied in learning best data management practices. After gathering the raw data, you will learn how to analyze and visualize this information using unique software products such as Tableau and Power BI. This wide array of developed skillsets can lead to a very promising career in:
• Data Scientist
• Data Analyst
• Database Manager
• Data Manager
• Systems Analyst
• Operations Analyst
• Data Consultant
Program Requirements
3
Core Courses
9 credits
+
4
Required Courses
12 credits
+
2
Elective Courses
6 credits
+
1
Thesis
Course
3 credits
=
10
Total Courses
30 credits
Technology/Database Core Courses
-
MDAN 623
Statistics for Data Analytics
- This course introduces univariate data analysis methods using statistics. Data visualization
methods and practices, and an overview of sampling techniques for data collection. Specifically,
this course teaches introductory statistical methods for the analysis and visualization of data
and basic concepts of probability theory. Course topics include descriptive statistics, data
visualization techniques, an introduction to statistical inference (confidence intervals and
hypothesis testing) for decision making, linear regression models, data sampling techniques. The
students will learn the statistical package SPSS to analyze data sets from real-world
applications.
3 Credits -
MSIN 627
Multi-Dimensional Analytics and Visualization Technologies
- The course introduces the practice of managing data as corporate assets by organizations to gain
competitive advantage and meet regulatory demand. The course will also describe the data
management emerging profession, and skills required to perform the various data management
functions for each role.
Prerequisite: MDAN 610
3 Credits -
MSIN 637
Principles of Data Analytics
- This course serves as an introduction to Data Analysis, primarily using the latest version of
Microsoft Excel. Microsoft Excel is a powerful tool used for a variety of purposes and in many
industries, and it can be harnessed to do impressive and powerful Data Analysis using its many
functions and features. Functions covered range from the simple SUM/SUMIF to more advanced
functions like INDEX and MATCH. Features covered range from simple to Data Tables, Pivot Tables,
Goal Seeking and Data Analysis Tool-pack and Solver. Analysis of Variance and Probability Theory
are also introduced.
3 Credits
Technology/Database Required Courses
-
MSIN 614
Data Transformation, Migration and Integration
- This course combines lectures with hands-on labs to teach students necessary skills to install,
upgrade, manage & administer SQL Server instances and databases for performance, high
availability &Disaster Recover. Topics covered in the class will include System Databases, Data
Files, Log Files & Check Points, Memory CPU and Disk Redundancy Discussions, indexing and query
optimization, Database backup and restoration, Log Shipping, Database Mirroring, Database
Replication, Database Snapshots, Security, Policy Based Management, SQL Agent, Task Scheduling&
Automation, Database Mail, Database Maintenance Plans, Monitoring, Alerting & Tuning, Blocking
Transitions & Dedicated Administrator Connection.
Prerequisite: MSIN 615
3 Credits -
MSIN 615
Database Management and Administration Technologies
- This course provides students with a solid foundation in database management and design concepts
and related skills. The course will explore database design techniques such as Entity
Relationship modeling, normalization, database modeling/design tools such as Microsoft Visio or
MySQL Workbench and UML, database implementation techniques using SQL Server Express. Students
will learn how to examine user requirements and design and implement a database that supports
the requirements and helps enforce the business constraints. Students will utilize various
techniques to identify and correct errors that exist in proposed database designs. Students will
design and implement databases and use SQL to construct simple and nested queries and inner
joins to retrieve and manipulate data. Students will become familiar with SQL Server Management
Studio, using it to implement and populate databases and test queries written in SQL.
Prerequisite: MDAN 610
3 Credits -
MSIN 616
Advanced Database Management and Data Analytics
- Building on Database Management and Administration, the course explores additional data modeling
techniques, concepts of database integrity and transaction management, stored procedures,
user-defined functions, database programming, query optimization, performance and tuning, and
other advanced SQL topics.
Prerequisite: MSIN 615
3 Credits -
MSIN 677
Advanced Data Visualization
- In this course, students will explore data analytics and visualization. The course will begin by
reviewing analytical methods with an emphasis on the art of crafting compelling data stories.
Through lectures, demonstrations, and hands-on tutorials, students will learn how to transform
datasets into visualizations and dashboards that communicate key findings and that utilize
visual design principles. By the course's end, students will be equipped to present insightful,
data-driven narratives that enable decision-makers to discern trends and make informed
choices.
Prerequisite: MSIN 627
3 Credits
OR
-
MSIN 678
Business Intelligence Through Data Visualization and Power BI
- This course combines lectures with hands-on labs to teach students necessary skills to connect
to Various Data sources, Transform Data, Design Data Models, create, manage, and format
Charts/Visuals/DashBoards using various data sources e.g. excel files, SQL Server Databases, and
MS Access databases etc. of various complexities & Work with Filtering
Students will start with connecting to Datasources, transform data, design models and create
simple charts and move onto designing more complex Models and charts of various types including
analyzing data over time, trends analysis etc. Advanced formatting, DAX expressions and
Filtering will be utilized to make charts stand out.
Prerequisite: MSIN 627
3 Credits
Technology/Database Elective Courses
-
MSIN 620
Data Warehousing and Data Mining
- This course combines lectures with hands-on labs to teach students necessary skills to
administer SQL Server instances and databases. Topics covered in the class will include System
Databases, Data Files, Log Files & Check Points, Memory CPU and Disk Redundancy Discussions,
Functions, Stored Procedures, Triggers, indexing and query optimization, Database backup and
restoration, Log Shipping, Database Mirroring, Database Replication, Database Snapshots,
Security, Policy Based Management, SQL Agent & Task Scheduling/Automation, Database Maintenance
Plans, Monitoring, Alerting & Tuning, New Features, Blocking Transitions & Dedicated
Administrator Connection.
Pre-or Corequisite: MSIN 614 & MSIN 615
3 Credits -
MDAN 621
R for Data Analytics
- Students will learn about the basics and fundamentals of R programming/syntax to eventually
being able to write R scripts. R will be used to solve problems related to data. Students will
learn to assign variables and perform simple operations with vectors. Students will also learn
about lists, matrix, arrays and data frames. To complete the basics, the course will cover
conditional statements, functions, classes and debugging. Students will advance to reading and
writing data in R, in either table format (CSV, Excel) or in a text file (.txt). Finally,
students will cover important functions for character strings and dates in R.
3 Credits -
MDAN 622
Python for Data Analytics
-
This course introduces the basics of the python programming environment, including fundamental
python programming techniques such as lambdas, reading and manipulating csv files, and the NumPy
library. The course will introduce data manipulation and cleaning techniques using the popular
python pandas data science library and introduce the abstraction of the Series and DataFrame as
the central data structures for data analysis, along with tutorials on how to use functions such
as group by, merge, and pivot tables effectively. By the end of this course, students will be
able to take tabular data, clean it, manipulate it, and run basic inferential statistical
analyses.
Pre-or Corequisite: MDAN 608 & MDAN 610
3 Credits -
MSIN 626
Principles and Applications of Data Security
- This course explains why database security is becoming increasingly important and critical to
businesses and individuals. It demonstrates different methods/approaches that can be used to
compromise the data in a database and what types of remedies can be applied. It addresses the
underlying concepts of security and shows how database security can be realized by implementing
Windows OS security, network security, SQL Server security and Web application security. It
describes how auditing is used to help implement database security. It illustrates how a robust
backup and recovery plan can help secure a database. Students will implement database security
using Windows OS and SQL Server.
Prerequisites: MSIN 615
3 Credits -
MSIN 633
Data Modeling, Analysis, and Visualization - Alteryx
- This course combines lectures with hands-on labs to help students understand transaction
systems, data warehouses, fact and dimension tables, design custom columns, custom tables and
create multi-dimensional data models based on a wide variety of data sources. Dashboards and
widgets of varying complexities will be created using hierarchies, expressions, and functions
for data analysis, visualization and decision support.
Prerequisite: MSIN 616
3 Credits -
MSIN 664
Artificial Intelligence: Principles and Practice
- This course explores the fundamentals of Artificial Intelligence (AI) and applicable AI terms, introduces the students to Machine Learning and Prompt Engineering concepts, Generative AI and Large Language Models, fundamentals of AI Algorithms, why consider leveraging AI in Cloud, and responsible AI (emphasizing ethical considerations) in AWS and Azure.
MDAN 610
3 Credits
Technology/Database Thesis Courses (Choose 1)
-
MDAN 615
Data Analytics Internship
- This course provides students with the opportunity to work as an intern in the Data Analytics
area, and then to formulate a paper or project based on the approved internship. The internship
must be pre-approved and should provide the student with the ability to combine his/her
conceptual, technical, and applied knowledge in a business environment. This internship should
draw on the skills and knowledge gained throughout the program. Regular progress reporting is
expected throughout the internship. International students are required to apply for CPT for
eligibility to work during their internship. The Internship MUST be approved in advance by the
Program Chair. At the end of the internship, the student will be expected to take and pass a
recognized certification test to show competency in an aspect of Data Analytics.
Pre- or Corequisite: Permission of the Program Chair
3 Credits -
MDAN 617
Advanced Research in Data Analytics
- The Advanced Research course is designed to give students an individualized research, project
including reading and reporting on a specific topic approved by an instructor. The subject,
topics and related material must be relevant and advanced regarding data analytics either from a
technology perspective or from a business perspective depending on the student's area of
concentration.
3 Credits
Technology/Database Preparatory Courses
Students with insufficient background in computer science or information systems degree, will be required to complete some or all of these courses:
-
MSIN 511
Technology Concepts and Essentials
-
The IT Essentials (ITE) curriculum emphasizes practical experience to help students develop
fundamental computer and career skills. ITE helps students prepare for entry-level career
opportunities in ICT and the CompTIA A+ certification. The course also provides a learning
pathway to Cisco CCNA .
1 Credit -
MBAN 503
Introduction to Statistics
- This course is structured to enable students to develop and increase their competence in the
broad area of statistics and quantitative analysis. Each PowerPoint module will provide
definition of terms, the statistics, examples of applied usage & its interpretation. External
readings and audiovisual recordings of key concepts will also be required.
1 Credit -
MDAN 608
Introduction to Programming (Python)
-
This course introduces core programming basics—including data types, control structures,
algorithm development, and program design with functions—via the Python programming language.
The course discusses the fundamental principles of Object-Oriented Programming, as well as
in-depth data and information processing techniques. Students will problem solve, explore
real-world software development challenges, and create practical and contemporary applications
using graphical user interfaces, graphics, and network communications.
3 Credits -
MDAN 609
Introduction to Analytical Processes (Excel)
- This course will allow the student to comprehend and appreciate creating and working with excel
lists. Using multiple worksheets and workbooks. Applying excel editing and web tools. Developing
an excel application. Students will use tutorial lab exercises to grasp the above excel
concepts.
1 Credit -
MDAN 610
Introduction to Database
- This course covers the database concepts that are the foundation and building blocks of sound
database design and management. It explains why good database design is critical to the accurate
and efficient storage and retrieval of data. The course will explore database design techniques
such as database models, database modeling/design tools. The course identifies the functions
provided by a database management system to help ensure the integrity of data. It teaches
students how to design a database that maximizes data integrity using normalization techniques.
It also covers the use of SQL to create and populate tables and retrieve and update data.
3 Credits