NCCU Online: BS in IT, Data Analytics Concentration Flight Path Program

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Focus Your IT Education in Data Analytics

What if your job was to dive deep into large datasets and find key insights that drive impactful decisions? The NCCU Online: Bachelor of Science in Information Technology (BS in IT) Flight Path Program provides the training you need to become an in-demand technology expert, and the Data Analytics concentration teaches you the tools and techniques for an exciting career in data science.

Through NCCU Online: Flight Path Program’s intentional approach to virtual learning, you’ll experience the support you need to thrive in your studies and advance your career. We offer a career-focused curriculum, personalized attention, and immersive courses that position you for success — both academically and professionally.

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What Is a Data Analytics Concentration in Information Technology?
The NCCU Online: Bachelor of Science in Information Technology (BS in IT) Flight Path Program empowers you to drive innovation in tech and boosts your employability through individualized guidance and industry-relevant instruction. Focusing your studies with the Data Analytics concentration will augment your learning by teaching you valuable skills in data-driven decision-making, involving the collection, processing, analysis, and visualization of large datasets.
By choosing this concentration, you’ll acquire an in-demand skill set to perform in-depth data analysis, including:

  • Competency in statistical analysis and predictive modeling

  • Proficiency in data mining techniques and tools

  • Skills in interpreting and visualizing data to provide actionable insights

  • Understanding of data governance and data quality management

Focus on Data Analytics Careers

As more organizations rely on big data to drive growth and sustainability, the need for skilled data analytics professionals continues to surge. According to Precedence Research, the data analytics market is projected to grow from $50 billion in 2024 to $659 billion by 2034, indicating a substantial compound annual growth rate (CAGR) of 29.4%.

Take a look at some potential careers you can pursue with NCCU Online’s Bachelor of Science in Information Technology (BS in IT) with a Data Analytics concentration:*

Data Architect

Average Base Salary: $132,772

Machine Learning Engineer

Average Base Salary: $$121,988

Database Administrator

Average Base Salary: $82,184

Business Intelligence Analyst

Average Base Salary: $77,503

Curriculum & Courses

The BS in IT requires 36 hours of general education courses and 27 hours of information technology courses, with between 32 and 36 core business credit hours. The data analytics concentration requires a combination of 21 credit hours in concentration-specific electives and four credit hours in general electives.

Keep in mind that you’re required to transfer in with at least 24 credit hours and any additional transfer credits may significantly reduce your required hours to graduate.

The required Data Analytics concentration courses include:

STQM 4000 Data Analytics in R – 3 Credit Hours

The goal of this course is to provide background in the R programming language and how this software can be successfully applied in business analytics and related disciplines. We start from the basics of downloading, installing, and running simple algorithms in R and go further by building the necessary skills and capabilities for the student to be able to perform successful data analysis. We will touch on topics such as database construction and handling, visualization, and exploratory data analysis. We will also cover the basic preparation of datasets, and introduce students to simple examples that can be solved using the algorithms designed during the course. The main purpose of this course is to provide the audience with knowledge and skills for writing structured computer programs that will be helpful in handling practical programs.

STQM 4010 Modeling and Optimization for Analytics – 3 Credit Hours

This course will provide a broad perspective and a systematic approach to practical problem analysis and optimization. The overall goal is to provide an introduction to the use of mathematical concepts and models in managerial decision-making. Operations research techniques are presented in the context of planning, operations, marketing, management, and other areas. In this course, students will learn how to create mathematical models and solve them using linear programming, network programming, integer programming, and other methods for dealing with deterministic and stochastic problems.

STQM 4020 Applied Time Series Analysis – 3 Credit Hours

This course will focus on time analysis, modeling, and forecasting, with emphasis on practical applications in business and other areas. Throughout the course, we will use real data sets from various sources. This course will use R or another professional software for most of the applied statistical analysis. Data analysis usually involves getting data, parsing the data, and transforming the data to a state where you can apply time series analysis. Upon completion of the course, the students will be able to carry out basic time series analysis and fit a model to data. Our goal is to enable students to learn from data to gain useful predictions and insights.

STQM 4030 Computational Statistics Using SAS – 3 Credit Hours

The course presents material on Statistical Analysis System (SAS) programming and its use in conjunction with some intermediate statistical methods in dealing with business problems. By the end of the course, students should be able to formulate business problems, write SAS programs, conduct some common statistical procedures (using SAS), and report the findings.

STQM 4420 Applied Regression Analysis – 3 Credit Hours

This course covers applied regression and other multivariable methods in data analysis. Topics covered include simple linear regression, multivariable regression, inference, transformations, correlation, dummy variables, regression diagnostics, polynomial regression, analysis of variance, analysis of covariance, and selecting the best model.

STQM 4440 Applied Categorical Data Analysis – 3 Credit Hours

This course covers methods of data analysis for data that is categorical in nature. Topics covered include contingency tables, association, Mantel-Haenszel test, observer agreement, ANOVA on ranks, and logistic regression.

STQM 4900 Special Topics in Data Analytics – 3 Credit Hours

Content may vary with each offering of this course. Interested students must consult with an instructor or department chair prior to enrolling. Topics covered include statistical computing, simulation, survival analysis, cluster analysis, factor analysis, nonparametric statistics, and econometrics. This course may be repeated for credit.

Is a Concentration in Data Analytics Worth It?

The demand for data analysts is robust and continues to grow. The U.S. Bureau of Labor Statistics (BLS) projects a 36% increase in employment for data scientists through 2033, much faster than the 4% average for all occupations. This growth reflects the increasing reliance of businesses on data-driven decision-making across industries and sectors including finance, health care, marketing, and technology.

By pursuing a data analytics concentration, you can also be well positioned for competitive salaries. The average data analyst salary is almost $70,000 annually, with salaries ranging up to $94,000 based on location and experience. The degree could also open doors for higher-level roles such as data scientists, who earn an average salary of over $102,000.*.

With a BS in IT degree and a Data Analytics concentration in hand, you’ll be equipped to meet the growing demand for professionals who can interpret complex data and provide actionable insights, making you a valuable asset in today’s data-driven world.

Explore the NCCU Online: Flight Path Programs

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*General labor market and salary data are sourced from Payscale. Salary and employment outcomes vary by geographic area, previous work experience, education, and opportunities for employment. ECU does not guarantee employment placement, salary level, or career advancement. Additional training and experience may be necessary for leadership positions.

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