Bachelor's Degree

Data Analytics
Online Bachelor's Degree Program

CLASSES START
Jul 8th

32 Mo.

Program Length

120

Credits

Online

Format

MBA

Dual Credit

Waived Enrollment Fee

Apply Now Request Information

Bachelor's Degree

Data Analytics
Online Bachelor's Degree Program

Walk a new, exciting career path in data analytics

Accreditation	Accredited by the Higher Learning Commission
Transfer credit	Up to 90 approved credits
Format	100% online classes you can take right at home
Certification	Prep for Certified Entry-Level Python Programmer (PCEP) certification, and more from Cisco, Microsoft and CompTIA—built-in as part of tuition!¹
Pathways	Earn dual credit towards an MBA degree program
QuickPaths	Transfer credit, stackable credentials, and adaptive learning technology build a faster pathway to a higher education with Herzing University

US News Best Online Programs Bachelor's 2024 Badge

Overview: Data Analytics Bachelor's Degree Program (IT)

The Bachelor of Science in IT with a concentration in Data Analytics is a 120-credit undergraduate program which prepares you for entry-level jobs as a data analyst.

The online degree program provides students with fundamental knowledge and skills in statistics, programming, data presentation and visualization, data management, and much more.

Career-focused curriculum

Discover the crucial knowledge and skills required to succeed in your work and build a foundation for continued career growth.

Flexible schedule

You can take classes during the day or in the evening. We strive to be as flexible as possible for busy non-traditional students.

Virtual services

Access to extensive virtual services, including academic advising, tutoring, support services, technical support and library services.

Lifelong support

We support your ongoing career advancement by providing comprehensive, personalized student services with lifelong career coaching.

Rolling admissions

No application deadlines to worry about. Apply when you’re ready and prepare to get started soon.

Classes Start July 8th

Learn More Today

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Curriculum

Data Analytics program classes & curriculum details

Our program is designed to help you develop crucial competencies in data analytics, emphasizing in the fundamentals of IT to position you for a wide variety of job possibilities.

The bachelor’s degree plan includes 24 credit hours in required data analytics classes and 6 elective credit hours in the field of IT, information systems, computer science or a related discipline.

All classes are delivered online with a required capstone project or internship.

Program	Monthsⁱ	Credits
Bachelor of Science in Information Technology with a Concentration in Data Analytics Technology	32	120

i. Average number of months for students to complete program
Program availability varies by location

Required Courses in Information Technology

All courses, 49.00 semester credit hours, are required.

IS 122 - Programming Logic 3.00

This course provides instruction in fundamental object-oriented programming concepts. Topics include problem solving and algorithm development, programming standards, variables, data types, operators, decisions, repetitive statements, modularity, methods, attributes, objects, classes, arrays, file I/O, and software testing and debugging, all within an object-oriented programming framework. Concepts may be introduced with a visual tool. Topics are demonstrated and implemented in a higher-level contemporary language such as Java or C#.

IS 123 - Computer Networks 3.00

This course provides instruction in network design and technologies using the Open Systems Interconnection (OSI) model. Topics include network fundamentals, the OSI model, network operating systems, TCP/IP fundamentals and utilities, network installation and upgrades, network remote access configuration and protocols, network administration and security, fault tolerance and disaster recovery considerations and procedures, and network troubleshooting procedures.

or IS 195 Transition to Technology Concepts *
* IS 195 is required of advanced standing students only.

IS 183 - Database Concepts and Applications I 3.00

This course provides an introduction to fundamental principles and guidelines for designing, developing, and implementing secure relational databases. Topics include: Database as a Service (DBaaS); entity relationships as foundations of relational database design; ensuring data integrity; the use of standard SQL as a means of developing complex queries; and the use of comparison operators to customize data presentation for reporting.

IS 187 - Computer Architecture and Troubleshooting I 3.00

This course provides instruction in microcomputer software and hardware concepts using the latest technology and troubleshooting techniques. Topics include the function and purpose of hardware and software, system board components and memory management, working with floppy and hard drives, supporting input and output devices, multimedia technology, supporting operating systems, printers, and notebook computers, troubleshooting fundamentals, applying disaster-recovery techniques and developing maintenance plans, and working with networks and the Internet.

IS 192 - Linux Administration 3.00

This course introduces the capabilities and features of Linux as a multi-user operating system. Topics include planning and installing a Linux system, using and managing desktop interfaces, working with Linux shells and text files, performing system administration and management tasks such as file system management, application, process, and module management, network services installation and configuration, system security evaluation and enhancement, performance tuning, and troubleshooting techniques.

IS 283 - Network Security 3.00

This course introduces basic security principles, such as establishing an effective security policy, and the different types of hacker activities that are most likely to be encountered. It will instruct the student in the latest security industry recommendations and how to properly protect leading OS servers in a variety of settings as well as how to conduct security audits.

IS 285 - Routers and Switches I 3.00

This course introduces part one of concepts and procedures required to utilize industry standard switches and routers in multi-protocol internetworks. Topics include exploring router components and their function, configuring routers according to the industry standard operating system (OS), routing fundamentals in a subnetted network infrastructure, and LAN design technologies. The class focuses on the TCP/IP protocol suite and IP addressing in regards to function and importance in a routed environment. Routing protocol basics, such as static and dynamic routing techniques, are covered, with extensive labs and hands-on exercises.

IS 287 - Routers and Switches II 3.00

This course is a continuation of the Routers and Switches I course and is based on current industry standards. The focus of the course will cover topics such as switching basics, intermediate routing, introduction to VLSM (variable length subnet masking), scaling IP addresses, route flapping, RIP version 2, Enhanced Interior Gateway Routing Protocol implementation, switching concepts in regards to LAN design, VLAN configuration, and VLAN trunking techniques. The class also explores the leading industry standards associated with WAN communication technologies and design such as ISDN, PPP, and Frame Relay operations.

IS 293 - Linux Application Server 3.00

This course is a study of intermediate to advanced topics regarding Linux server-based applications. Topics include advanced Linux system administration, using Linux as an e-mail server, FTP server, database server, web server, and news server. Topics will also discuss implementing Linux services including DHCP, DNS, NIS, firewall, and network security.

IS 296 - Python Programming 3.00

This course covers the Python programming language. Topics include the basic elements of programming, variables, assignment statements, built-in data types, conditions, loops, arrays, and I/O. This class covers programming skills such as algorithm development, and program design with functions. It also includes an introduction to object-oriented programming and GUI programming concepts and topics.

IT 120 - Technical Writing 1.00

This course is designed to help students develop skills that will enable them to produce clear and effective scientific and technical documents. Focus will be on basic principles of good writing-which scientific and technical writing shares with other forms of writing-and on types of documents common in scientific and technical fields and organizations. While the emphasis will be on writing, oral communication of scientific and technical information will form an important component of the course, as well. The processes and techniques used to produce manuals and other supporting documents to communicate complex and technical information more easily will be explored.

IT 346 - Information Technology Project Management 3.00

This course covers techniques and managerial concepts of information technology project management. It prepares students to manage complex information technology projects. Students are introduced to all five major process groups in project management, namely initiating, planning, executing, monitoring, controlling, and closing. Topics include project life cycles, cost benefit analysis, work breakdown structure, staffing, roles, responsibilities, accountability, finance, estimation, budgeting, planning, risk management, scheduling, and tracking. The course also introduces students to computer software for project management. Students will work in teams to design a project plan for a real-world IT project that demonstrates an ability to follow standard project management methodology.

** Completion of IT 346 Information Technology Project Management may be waived with the permission of the Director of Campus Operations/Academic Dean for Online Learning if the student has already completed BU 345 Project Management.

IT 368 - Cloud Computing 3.00

This course develops knowledge and skills in cloud computing. Students will learn cloud computing principles, architectures, and implementations. Topics include cloud computing history, principles, architectures, and implementations, cloud services and solutions, virtualization, network infrastructure and access, data storage, security, end-user access, and standards and compliance.

NT 181 - Network and Server Operating Systems 3.00

This course develops knowledge and skills in Microsoft Windows client and server operating systems. Topics include installing the client and server operating systems, planning, installing, managing, and troubleshooting server roles, features, and network services, implementing and conducting administration of resources, implementing, managing, and troubleshooting hardware devices and drivers, monitoring and optimizing performance, reliability and availability, managing, configuring, and troubleshooting storage use, configuring and troubleshooting the desktop environment and network connections, implementing, managing, and troubleshooting network protocols, and implementing, monitoring, and troubleshooting security.

NT 201 - Network Infrastructure Administration 3.00

This course is designed to provide instruction in implementing and administering a modern network infrastructure. Topics include installing, configuring, managing, monitoring, and troubleshooting domain name services, network protocols, Windows Internet Name Services (WINS), Internet Protocol Routing, network address translation (NAT), and Certificate Services.

NT 306 - Virtualization 3.00

This course provides instruction in computer operating system virtualization concepts and practices. Topics include business and performance benefits of virtualization, local and network storage management, creating and managing stand-alone virtual machines, cloning virtual machines, virtualization in the network operations center, software and network testing using virtualization, virtualization as a disaster recovery tool, and managing and tuning virtual machine and virtual infrastructure performance. Emphasis is placed on learning several virtualization environments and approaches, both proprietary and open-source. Concepts will be illustrated and enforced with a variety of actual installations and practical projects.

NT 326 - System Administration Scripting 3.00

This course provides an introduction to automating administrative tasks using scripts. Students will design and implement scripts of moderate complexity that automate administrative tasks such as the creation of user accounts, the administration of disk drive and printer, and the management of system services and event logs. Scripts may be written using languages such as Bourne and C, and Korn shells and JScript, VBScript, and Perl. Topics include tools and utilities, interactive command line programs, shell programming using constructs, variables, commands, functions, and debugging processes.

Required Courses in Technical Specialty Domain - Data Analytics

All courses, 24.00 semester credit hours, are required.

DA 301 - Statistics for Data Analytics 3.00

This course includes topics fundamental to understanding statistics methods used in the field of data analytics. Topics include probability, descriptive statistics, inferential statistics, regression and linearly uncorrelated variables (PCA).

DA 302 - Foundations of Data Analytics 3.00

This course provides the practical key techniques and tools used in data analytics, including the concepts, principles and practical applications that are relevant to the industry and technology environment. Learning will be supported and explained using open-source software, including Apache Hadoop, MapReduce and R. Students will have the opportunity to understand how these methods and tools are applied to real-world business challenges, including the analyses of data generated from IoT devices.

DA 304 - Python for Data Analytics 3.00

This course includes data analysis techniques using the Python programming language. That includes knowing how to import data, explore data, analyze data, learn from data, visualize data, and ultimately generate shareable reports. This course also introduces you to machine leaning, a powerful area of data analysis. This course introduces a collection of powerful, open-source tools including Python, Jupyter notebooks, pandas, and matplotlib.

DA 306 - R Programming for Data Analytics 3.00

This course teaches R, an open-source programming language for statistical computing and graphics. Topics include how to write functions, loops, and scripts that uses basic statistical functions and tools such as normal distribution, boxplots to analyze data and present data in a graphical way, demonstrating how to turn unstructured data into structured data, how to live link R to a database, and how to search online databases for answers.

DA 402 - Data Analytics and Projects I 3.00

This project-based course focuses on a big data analysis solution using cloud services. Topics include creating clusters to process big data, connecting to clusters, uploading data, and running codes. Other projects include using tools for analyzing and querying data in a distributed environment, using user-defined functions and incorporating predictive analytics and machine learning.

DA 404 - Data Analytics and Projects II 3.00

This project-based course presents Machine Learning technology. Advanced topics include using machine learning tools and algorithms to gather data, clean data, create data models, perform prediction, and process new data.

DA 408 - Data Management 3.00

This course includes the topics of advanced database management and reporting, and business intelligence (BI). This course is intended to teach a managed enterprise BI solution. Additional topics include how to implement multi-dimensional and tabular data models, delivering reports with industry standard tools, creating dashboards with industry standard tools, and discovering business insights by using data mining.

DA 410 - Data Presentation and Visualization 3.00

This course teaches data presentation and visualization. The topics include the learning of building blocks and services; connecting to data sources; cleaning and transforming of data; modeling data and managing your data relationship; creating calculated columns, measures, and tables; creating customized visualization; connecting and publishing and sharing dashboards and reports.

Elective Courses in Information Technology

A minimum of 6 semester credit hours in the field of information technology, information systems, computer science or a related discipline are required.

Required Capstone or Internship

All courses, 3.00 semester credit hours, are required.

IS 495 - Internship 3.00

This is an elective course in bachelor's programs that students may take in their final semester. The career internship course is designed for students interested in pursuing a career in the computer science and information technology fields. The outcome of the internship is an informed student fully apprised of the opportunities their program offers for professional growth. During the internship, the student will experience various aspects of working in the actual field in which the student has been educated. The internship is designed to provide the student with the opportunity to experience and participate in duties typical of a contemporary workplace setting. Student learning centers on observing experienced personnel as well as participating in actual hands-on procedures under close supervision of trained professionals.

IT 491 - Information Technology Capstone Project 3.00

Students work individually or in project teams on an industry-sponsored or instructor-approved project. They will identify a problem, develop design specifications based on stakeholder needs, consider alternative designs, develop a schedule and/or budget, and design, develop, and test the proposed process or product. Interim reports to the sponsor or to the class, a final project report, and a final presentation will be required.

Required Courses in General Education

Students enrolled in this bachelor's degree must complete a minimum of 36.00 semester credit hours in general education distributed among the following disciplines. Refer to the General Education section of the catalog for specific information about courses within each discipline. 12.00 Semester Credit Hours in Communications 9.00 Semester Credit Hours in Humanities (must include 3 semester credit hours of cultural diversity) 6.00 Semester Credit Hours in Mathematics 3.00 Semester Credit Hours in Science 6.00 Semester Credit Hours in Social and Behavioral Sciences

Personal and Professional Development Courses

A minimum of 2.00 semester credit hours is required.

PD 121 - Professional Development I 1.00

This course is designed to introduce students to methodologies that will prepare them for academic and professional success. Topics include but are not limited to Canvas support, student support services, e-books, university policies, resumes, self-reflection, time management, goal setting, and strategies for anxiety reduction.

PD 202 - Professional Development II 1.00

This course provides an opportunity for students to critically examine their skills and develop a plan to further their career and own financial literacy. Topics include research, job searching, developing career documents, refining interview and communication skills, and creating a personal budget.

Dual Credit

Save time and money by earning dual credit

Students enrolled in Herzing University’s IT Bachelor of Science with a Concentration in Data Analytics program can get a head start on earning a Master of Business Administration (MBA).

Qualifying undergraduate students who pursue a data analytics concentration bachelor’s degree may apply up to 12 credits toward an MBA degree.

U.S. News Best Online Bachelor's Degree Program 2021

Data Analytics Bachelor's Degree Certification Eligibility

What certifications can I pursue?

The “Python for Data Analytics” course includes prep for the Certified Entry-Level Python Programmer (PCEP) exam—and we’ll pay for your first attempt.

The Python programming language is a key component of our curriculum, given its top-ranking popularity and utility as a widely adopted tool for big data analysis. College-level coursework in Python can help you build a great foundation in a programming language you’ll be able to use throughout your data analytics career.

Our IT-focused curriculum also prepares you for certifications from Cisco, Microsoft and CompTIA—also built-in as part of your tuition!

Tuition & Cost

The cost of tuition for the Bachelor of Science in Information Technology with a Concentration in Data Analytics Technology program is $515 per credit.

You can potentially earn even greater savings by transferring credit from prior college coursework, applying for financial aid, or potential partnership opportunities through your employer.

Our goal is your career advancement. That’s why we are always working to improve our curriculum and processes to make our program as affordable as possible while preparing you best for success in your work.

View Tuition Wizard

Scholarships & Financial Aid

You may be eligible for multiple scholarships and grants, both through Herzing University and several national scholarship websites.

Find scholarships and grants

Military/Veteran Discounts

Veterans, Active Duty U.S. Servicemembers, and spouses may qualify for a 10% tuition discount or tuition reduction to $250 per credit.

VA/Military benefits

Requirements

Enrollment prerequisites

Requirements to enroll in the Herzing University Data Analytics bachelor’s degree program include:

Completed high school diploma, GED or equivalent
Meet and interview with a Herzing University admissions advisor
Complete an enrollment application

With Herzing University advancing your career IS possible. We are here to help you take the first step.

Eligible states for enrollment: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming, District Of Columbia, and the Virgin Islands.

Classes Start July 8th

Waived Enrollment Fee

Apply Now Request Info

Pathways

Your career path in data analytics

Developing a strong foundation in business analytics, database management, statistics and basic programming opens many professional doors across all major industries.

Potential job titles in data analytics include:

Computer and Information Systems Manager
Computer Network Architect
Business Data Analyst
Database Administrator
Data Manager

How can I advance my career? After earning an undergraduate degree, you can potentially explore many opportunities at the graduate level, including a Master of Business Administration (MBA).

Job outlook

A data analyst’s broad skillset provides them with potential qualification for a wide variety of jobs, many of which are projected for growth in the near future.

According to the Bureau of Labor Statistics (BLS), employment in data analyst-related jobs is expected to rise higher than average from 2019—from a from a 7% projected increase for Computer Systems Analyst to a 25% projected increase for Operations Research Analysts.*

Locations

Program Finder

Data Analytics Degree Programs

Showing 1 programs for the Online campus

On Campus| Online

This program prepares students for a broad range of positions in the field of information technology. Foundational skills taught include end-user support, client/server operating systems, network infrastructure administration, security, scripting, database fundamentals, cloud computing, virtualization, data storage and technical communication. Advanced skills include database design, project management, information technology management and business systems analysis. Coursework in this program provides a foundation for select industry certifications. These certifications enhance employment opportunities but are not a state specific requirement.

Additional skills in data analytics technology include big data foundations, data analytics technologies, statistics for data analytics, data mining and analysis, data management and data presentation and visualization.

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Computer Programming

Cybersecurity

Business analyst smiling with team during weekly meeting

Business Analytics

Disclosures

Accreditation & Disclosures

1. Certification in this program is not a state requirement.

Herzing University is accredited by the Higher Learning Commission (hlcommission.org), an institutional accreditation agency recognized by the U.S. Department of Education.

View Herzing University Accreditation and Approvals

* Bureau of Labor Statistics (BLS), U.S. Department of Labor, Occupational Employment and Wage Statistics 2023 / Occupational Outlook Handbook 2022. BLS estimates do not represent entry-level wages and/or salaries. Multiple factors, including prior experience, age, geography market in which you want to work and degree field, will affect career outcomes and earnings. Herzing neither represents that its graduates will earn the average salaries calculated by BLS for a particular job nor guarantees that graduation from its program will result in a job, promotion, salary increase or other career growth.

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Data Analytics
Online Bachelor's Degree Program

Data Analytics
Online Bachelor's Degree Program

Walk a new, exciting career path in data analytics