Study Synchronously Online or On Campus: It's Your Choice
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
Technology/Database Core Courses
Database Concepts and Design
- 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.
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.
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.
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.
Technology/Database Required Courses
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.
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.
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
Technology/Database Elective Courses
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 616
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.
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.
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 & MSIN 616
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
Advanced Data Visualization
- This course starts with an introduction to Transactional Databases vs. Data Warehouse, Data Marts, Big Data, No SQL Databases, fact and dimension tables and various tools to understand, analyze and visualize hidden information in Raw data. It combines lectures with hands on exercises and labs, using various components of Tableau and its visualization tools, to create charts, dashboards and stories containing visual presentation of data and their summaries to help make sense of huge collection of such raw data and to communicate the same to decision makers so they can quickly spot trends, see patterns and discover other pieces of information buried in such data to make day to day decisions quickly and efficiently.
Prerequisite: MSIN 615
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.
Technology/Database Thesis Courses (Choose 1)
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.
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.
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:
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 .
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.
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.
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.