The Business concentration builds skills that can be applied to all sizes of business operations. In the business
world, a Data Analyst works with data and databases from a financial perspective and a business management
perspective to increase profits and overall success of a company.
Under this concentration, students develop the skills in financial analysis, management, trend analysis, and risk modelling. This wide array of developed skillsets can lead to a very promising career in:
• Financial Analyst
• Business Analyst
• Risk Analyst
• Operations Analyst
• Marketing Analyst
• Business Consultant
• Financial Consultant
• Business Manager
Business 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.
Business Required Course
Data Analytics: History and Comparison of Software Tools
- Data analysis (rooted in statistics) and computer technology have been developing and affecting each other, ever since the advent of computing. As the collected data size gets larger, new methods of data analysis have been introduced in each stage, out of necessity. As data collection and computing gets even cheaper, we should continue to see breakthroughs in the area of big data.
This course provides the students with an understanding of the history of data analytics (which some say dates back to ancient Egypt), its evolution, its uses & applications, challenges, benefits, threats and its opportunities for growth/changes that can be made in the field. It also compares and contrasts the various software packages that are being used in business today.
Business Elective Courses (Choose 4)
Information Technology for Effective Management
Focuses on information technology management in the workplace. The course explores the role of information technology as a tool for communication and control of all functions of product or service providers. IT is examined from a variety of viewpoints including its position in the digital economy, concepts and management, and strategic information systems used to gain competitive advantage. Ethical issues such as abuse by employees and preservation of privacy are also examined. This course covers topics include hardware, software, system analysis, information systems, and databases.
- This course covers general statistical concepts related to business management. Students will work on basic statistical analysis using various numeric and algebraic techniques. Students learn the advantages and disadvantages of the various tools used in inferential statistics and when and how to apply those methods. Topics to be covered include: descriptive statistics, basic inferential statistics, analysis of variance methods and nonparametric statistics for categorical data.
Digital Marketing Analytics
- This course is meant to integrate a virtually frictionless system for moving from data to decision, action to results! The course will explore how to:
- use analysis to craft experiences that profoundly reflect customers’ needs, expectations, and behaviors
- measure real digital media ROI: sales, leads, and customer satisfaction
- track the performance of all paid, earned, and owned digital channels
- leverage digital data beyond PR and marketing: for strategic planning, product development, and HR
- start optimizing digital content in real time
- implement advanced tools, processes, and algorithms for accurately measuring influence
- make the most of surveys, focus groups, and offline research synergies
- focus new marketing investments where they’ll deliver the most value
- identify and understand important audiences across the digital ecosystem
Data Driven Decision Making: For Small Businesses
- This course’s focus is on how to use business data to make an impact on business performance. It will inform students on how to use data to reduce inventory, determine product and customer profitability, gain insight into customer ordering behavior, how to determine if your cash flow is getting better or worse, and determining if a business is becoming more or less efficient as it grows. The intent of this course is to show the students what is possible rather than teaching mathematical techniques. Using real-world case studies from various functional areas, from simple to the more advanced, the course will deliver a series of analytics using software that most businesses already possess, suitable for anyone wishing to take their business to the next level. The course will also examine the advantages and disadvantages of trying to build these capabilities in-house and will provide a realistic view of the challenges associated with analytics in the business world. Different data analysis and visualization tools will also be discussed.
Revenue Management and Pricing Analytics
- The practices of Revenue Management and Pricing Analytics (RMPA) use historical sales data to analytically estimate demand forecasts that are then used in optimization models to set and update capacity (or prices) through the various channels to specific customer segments in an attempt to maximize profits. The practice of segmentation has transformed the transportation and hospitality industries and are increasingly important in industries as such retail, telecommunications, banking, health care and manufacturing. However, while capacity-constrained industries such as the airlines and hotels typically optimize on the capacity to make available to each customer segment, price optimization (by customer segmentation in the forms such as seasonal time-based pricing; package-based pricing; channel-based pricing; and coupons, mail-in rebates, and promotion codes) is more frequently used for less capacity constrained industries such as retailing and banking. This course guides students & professional on how to identify and exploit revenue management and pricing opportunities in different business contexts.
Six Sigma: The DMAIC System
- The goal of this course is to assist professionals to turn their own Six Sigma projects into reality. This course will guide the students through all aspects of Six Sigma from identifying and defining a suitable project topic, to sustainably managing its success in the control phase. By demonstrating all of the necessary steps supported by a “Define, Measure, Analyze, Improve, Control” (DMAIC) software guide, it makes the application of the sequentially linked DMAIC tools transferable to typical Six Sigma business projects. This course will give students the knowledge and confidence to continue their studies to take the Green Belt certification.
Financial Risk Modelling
- Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. Financial Risk Modeling bridges this gap between theory and practice by constructing a financial model from scratch and providing a nuts-and-bolts guide to solving common financial models using Excel.
This course takes a variety of investment topics in the construction of Portfolio Models (i.e., efficient portfolio management and short sales, Variance-Covariance matrices, estimating betas and security market line, value at risk, option-pricing models, bonds and term structure of interest rates) and an introduction to Visual Basic for Applications (VBA) functions and applications.
Business 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.
Business 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.