A Data Management and Data Analytics Degree Program that will Prepare you for a Lucrative Career
In addition to increasing your earning potential and opportunities for advancement, earning your bachelor’s degree in data analytics/data management also puts you right at the center of turning raw data into usable information. This online data analytics degree program provides a solid background in database management as well as applications in data wrangling, analysis, and visualization. You'll also learn about leadership and management skills that will help you propel your career even further. In many degree programs, you would have to choose a degree in data management or a different degree in data analytics—at WGU, you can earn one degree that provides both! Best of all, since this degree in data management and analytics is fully online, you can continue to work and earn money while you pursue higher education.
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COURSES & COMPETENCIES
Data Management & Data Analytics Courses
Our Bachelor of Science Data Management and Data Analytics degree program was designed, and is regularly updated, with input from key experts on our Information Technology Program Council. In addition to core IT skills, the program focuses on data analysis, machine learning, Python, R, scripting and programming, and more.
Earning a bachelor’s degree designed by industry experts adds theoretical depth to the practical knowledge you already have. The experts who make up our IT Program Council know exactly what it takes for a graduate to be successful in the fast-paced, ever-changing world of cloud computing.
The B.S. Data Management and Data Analytics program is an all-online program. You’ll complete program requirements independently, with instruction and support from WGU faculty. You’ll be expected to complete at least 12 competency units for each 6-month term. Each course is typically three or four units. There’s no limit on the number of units you can complete each term, so the more courses you complete, the quicker you can finish your program.
This course elaborates on concepts covered in Introduction to Data Science, helping to develop skills crucial to the field of data science and analysis. It explores how to wrangle data from diverse sources and shape it to enable data-driven applications—a common activity in many data scientists' routine. Topics covered include gathering and extracting data from widely-used data formats, assessing the quality of data, and exploring best practices for data cleaning.
This course introduces students to the concepts and terminology used in the field of data management. Students will be introduced to Structured Query Language (SQL) and will learn how to use Data Definition Language (DDL) and Data Manipulation Language (DML) commands to define, retrieve, and manipulate data. This course covers differentiations of data—structured vs. unstructured and quasi-structured (relational, hierarchical, XML, textual, visual, etc); it also covers aspects of data management (quality, policy, storage methodologies). Foundational concepts of data security are included.
This course covers conceptual data modeling and provides an introduction to MySQL. Students will learn how to create simple to complex SELECT queries including subqueries and joins, and students will also learn how to use SQL to update and delete data. Topics covered in this course include exposure to MySQL; developing physical schemas; creating and modifying databases, tables, views, foreign keys/primary keys (FKs/PKs), and indexes; populating tables; and developing simple Select-From-Where (SFW) queries to complex 3+ table join queries.
Advanced Data Management enables organizations to extract and analyze raw data. Skillful data management allows organizations to discover and explore data in ways that uncover trends, issues, and their root causes. In turn, businesses are better equipped to capitalize on opportunities and more accurately plan for the future. As organizations continue to extract larger and more detailed volumes of data, the need is rapidly growing for IT professionals possessing data management skills. These skills include performing advanced relational data modeling as well as designing data marts, lakes, and warehouses. This course will empower software developers with the skills to build business logic at the database layer to employ more stability and higher data-processing speeds. Data analysts will gain the ability to automate common tasks to summarize and integrate data as they prepare it for analysis. Data Management is a prerequisite for this course.
Data System Administration provides students with foundational skills to become a Database Administrator (DBA). This course illustrates how DBA’s ensure businesses are able to leverage significant data to increase profitability and support key business functions. Topics include database management tools, account administration, recovery procedures, and maintenance through upgrades and migrations.
Version control is critical to maintaining software and enabling scalability solutions. A best practice for any programming project that requires multiple files uses version control. Version control enables teams to have collaborative workflows and enhances the software development lifecycle. This course introduces students to the basics of publishing, retrieving, branching, and cloning. There are no prerequisites for this course.
Introduction to IT examines information technology as a discipline and the various roles and functions of the IT department as business support. Students are presented with various IT disciplines including systems and services, network and security, scripting and programming, data management, and business of IT, with a survey of technologies in every area and how they relate to each other and to the business.
IT Foundations focuses mostly on hardware and will afford you the skills you need to support five core components: mobile devices; networking; hardware; virtualization and cloud computing; and network and hardware troubleshooting. These are essential skills to set up and troubleshoot any system. Whether you work in a data center or an office, most of your work as an IT professional will execute in a hardware platform; understanding the hardware layer of the IT infrastructure will allow you to work more efficiently, provide solutions for business requirements, and be a key contributor in your company. The course prepares learners for the CompTIA A+ Core 1 certification exam.
IT Applications explores personal computer components and their functions in a desktop system. Topics cover computer data storage and retrieval, including classifying, installing, configuring, optimizing, upgrading, and troubleshooting printers, laptops, portable devices, operating systems, networks, and system security. Other areas in this course include recommending appropriate tools, diagnostic procedures, preventive maintenance, and troubleshooting techniques for personal computer components in a desktop system. The course finishes with strategies for identifying, preventing, and reporting safety hazards in a technological environment; effective communication with colleagues and clients; and job-related professional behavior. This course is designed to build the skills to support four core components: operating systems, security, software troubleshooting, and operational procedures. These are core competencies for IT professionals from cloud engineers to data analysts, and these competencies will empower students with a better understanding of the tools used during their careers. The course prepares learners for the CompTIA A+ Core 2 certification exam.
The Introduction to Spreadsheets course will help students become proficient in using spreadsheets to analyze business problems. Students will demonstrate competency in spreadsheet development and analysis for business applications (e.g., using essential spreadsheet functions, formulas, tables, charts, etc.). Introduction to Spreadsheets has no prerequisites.
Scripting and Programming - Foundations provides an introduction to programming, covering basic elements such as variables, data types, flow control, and design concepts. The course is language-agnostic in nature, ending in a survey of languages and introduces the distinction between interpreted and compiled languages. There are no prerequisites for this course.
Introduction to Programming in Python provides the fundamentals of the Python language and its features to control program flow and to manipulate data sets. This course teaches how to develop Python scripts that extract and manipulate data from unstructured data sources. Python libraries including acquisition and configuration are also covered. Scripting and Programming Foundations and Web Development Foundations are prerequisites to this course.
Network and Security - Foundations introduces students to the components of a computer network and the concept and role of communication protocols. The course covers widely used categorical classifications of networks (e.g., LAN, MAN, WAN, WLAN, PAN, SAN, CAN, and VPN) as well as network topologies, physical devices, and layered abstraction. The course also introduces students to basic concepts of security, covering vulnerabilities of networks and mitigation techniques, security of physical media, and security policies and procedures. This course has no prerequisites.
Networks for undergraduates focuses on the general concepts and applications of computer operating systems and network topologies. The fundamental knowledge and skills gained in this course prepares students for the CompTIA Network+ (N10-008) certification exam. Network and Security – Foundations is a pre-requisite for this course.
IT Leadership Foundations is an introductory course that provides students with an overview of organizational structures, communication, and leadership styles specific to information technology in organizations. It also introduces students to some of the power skills that help make successful IT professionals, including time management, problem solving, and emotional intelligence. Students in this course explore their own strengths and passions in relation to the field. There are no prerequisites for this course.
In this course, students will build on industry standard concepts, techniques, and processes to develop a comprehensive foundation for project management activities. During a project's life cycle, students will develop the critical skills necessary to initiate, plan, execute, monitor, control, and close a project. Students will apply best practices in areas such as scope management, resource allocation, project planning, project scheduling, quality control, risk management, performance measurement, and project reporting. This course prepares students for the following certification exam: CompTIA Project+.
Business of IT—Applications examines Information Technology Infrastructure Library (ITIL®) terminology, structure, policies, and concepts. Focusing on the management of information technology (IT) infrastructure, development, and operations, students will explore the core principles of ITIL practices for service management to prepare them for careers as IT professionals, business managers, and business process owners. This course has no prerequisites. This course prepares students for the Axelos ITIL v4 certification exam.
This course introduces students to web design and development by presenting them with HTML5 and Cascading Style Sheets (CSS), the foundational languages of the web, by reviewing media strategies and by using tools and techniques commonly employed in web development.
Data and Information Governance provides students with the knowledge that establishing rules of engagement, policies, procedures, and data stewardship is essential to exercising organizational control over, and extracting maximum value from, its data assets. Good data governance helps an organization lower costs, create efficiencies, and achieve its strategic goals and objectives. Data governance provides a framework for properly managing information across the entire data lifecycle and establishes strategies in support of disaster recovery and continuity of operations. This course will prepare IT professionals to assist their organization in the definition and implementation of best practices related to the planning and implementation of managed systems that meet business, technical, security, auditing, disaster recovery, and business continuity requirements.
This course focuses on exploratory data analysis (EDA) utilizing R. EDA is an approach for summarizing and visualizing the important characteristics of a data set. Exploratory data analysis focuses on exploring data to understand the data's underlying structure and variables to develop intuition about the data set, to consider how that data set came into existence, and to decide how it can be investigated with more formal statistical methods.
Data Visualization covers the application of design principles, human perception, color theory, and effective storytelling in the context of data visualization. It addresses presenting data to others, and advancing technology with visualization tools enabling data scientists to share their findings and support organizational decision-making processes. Additionally, this course focuses on how to visually encode and present data to an audience.
This course covers the most common tools, techniques, and procedures involved in data analytics. Students will review all the disciplines involved with data analytics learned in previous courses and get a better understanding of how they all relate to one another.
This course introduces the data analysis process and common statistical techniques necessary for the analysis of data. Students will ask questions that can be solved with a given data set, set up experiments, use statistics and data wrangling to test hypotheses, find ways to speed up their data analysis code, make their data set easier to access, and communicate their findings.
Course Description This course presents the end-to-end process of investigating data through a machine learning lens. Topics covered include techniques for extracting data, identifying useful features that best represent data, a survey of commonly-used machine learning algorithms, and methods for evaluating the performance of machine learning algorithms.
Data Structures and Algorithms I covers the fundamentals of dynamic data structures, such as bags, lists, stacks, queues, trees, hash tables, and their associated algorithms. With Python software as the basis, the course discusses object-oriented design and abstract data types as a design paradigm. The course emphasizes problem solving and techniques for designing efficient, maintainable software applications. Students will implement simple applications using the techniques learned.
This course covers basic elements of technical communication, including professional written communication proficiency; the ability to strategize approaches for differing audiences; and technical style, grammar, and syntax proficiency.
In this course you will learn key critical thinking concepts and how to apply them in the analysis and evaluation of reasons and evidence. The course examines the basic components of an argument, the credibility of evidence sources, the impact of bias, and how to construct an argument that provides good support for a claim. The course consists of an introduction and four major sections. Each section includes learning opportunities through readings, videos, audio, and other relevant resources. Assessment activities with feedback also provide opportunities to check your learning, practice, and show how well you understand course content. Because the course is self-paced, you may move through the material as quickly or as slowly as you need to gain proficiency in the four competencies that will be covered in the final assessment. If you have no prior knowledge or experience, you can expect to spend 30-40 hours on the course content.
Welcome to Composition I: Writing with a Strategy! In this course, you will focus on three main topics: writing strategies, writing style, format and grammar, and editing and revising text. This course consists of an introduction and five sections aligned to the three main topics. The sections address understanding purpose and audience, writing strategies and techniques, format, style, structure, and grammar, editing and revision strategies, and constructive feedback. Each section includes learning opportunities through readings, videos, audio, and other relevant resources. Assessment activities with feedback also provide opportunities to check your learning, practice, and show how well you understand course content. Because the course is self-paced, you may move through the material as quickly or as slowly as you need to gain proficiency in the five competencies that will be covered in the final assessment. If you have no prior knowledge or experience, you can expect to spend 30-40 hours on the course content.
American Politics and the U.S. Constitution examines the evolution of representative government in the United States and the changing interpretations of the civil rights and civil liberties protected by the Constitution. This course will give candidates an understanding of the powers of the branches of the federal government, the continual tensions inherent in a federal system, the shifting relationship between state and federal governments, and the interactions between elected officials and the ever-changing electorate. This course will focus on such topics as the role of a free press in a democracy, the impact of changing demographics on American politics, and the debates over and expansion of civil rights. Upon completion of the course, candidates should be able to explain the basic functions of the federal government, describe the forces that shape American policy and politics, and be better prepared to participate in America’s civic institutions. This course has no prerequisite.
Applied Probability and Statistics is designed to help students develop competence in the fundamental concepts of basic statistics including: introductory algebra and graphing; descriptive statistics; regression and correlation; and probability. Statistical data and probability are often used in everyday life, science, business, information technology, and educational settings to make informed decisions about the validity of studies and the effect of data on decisions. This course discusses what constitutes sound research design and how to appropriately model phenomena using statistical data. Additionally, the content covers simple probability calculations, based on events that occur in the business and IT industries. No prerequisites are required for this course.
This course will discuss geographic concepts, places and regions, physical and human systems, and the environment.
Applied Algebra is designed to help you develop competence in working with functions, the algebra of functions, and using some applied properties of functions. You will start learning about how we can apply different kinds of functions to relevant, real-life examples. From there, the algebra of several families of functions will be explored, including linear, polynomial, exponential, and logistic functions. You will also learn about relevant, applicable mathematical properties of each family of functions, including rate of change, concavity, maximizing/minimizing, and asymptotes. These properties will be used to solve problems related to your major and make sense of everyday living problems. Students should complete Applied Probability and Statistics or its equivalent prior to engaging in Applied Algebra.
This introductory humanities course allows candidates to practice essential writing, communication, and critical thinking skills necessary to engage in civic and professional interactions as mature, informed adults. Whether through studying literature, visual and performing arts, or philosophy, all humanities courses stress the need to form reasoned, analytical, and articulate responses to cultural and creative works. Studying a wide variety of creative works allows candidates to more effectively enter the global community with a broad and enlightened perspective.
Ethics in Technology examines the ethical considerations of technology in each of four categories: privacy, accuracy, property, and access. The course presents a range of technologies and issues that challenge technologists in the field of information ethics. Students are introduced to a decision-making process as informed by ethical frameworks that outline key ethical considerations within the technologies presented. Students will study specific cases to help inform their professional responsibilities in how to navigate the important controversies in topics such as surveillance, social media, hacking, data manipulation, plagiarism and piracy, artificial intelligence, responsible innovation, and the digital divide. This course has no prerequisites.
This course provides students an introduction to using the scientific method and engaging in scientific research to reach conclusions about the natural world. Students will design and carry out an experiment to investigate a hypothesis by gathering quantitative data. They will also research a specific ecosystem using academic sources and draw conclusions from their findings.
This course provides students with an overview of the basic principles and unifying ideas of the physical sciences: physics, chemistry, and earth sciences. Course materials focus on scientific reasoning and practical, everyday applications of physical science concepts to help students integrate conceptual knowledge with practical skills.
Welcome to Introduction to Communication: Connecting with Others! It may seem like common knowledge that communication skills are important, and that communicating with others is inescapable in our everyday lives. While this may appear simplistic, the study of communication is actually complex, dynamic, and multifaceted. Strong communication skills are invaluable to strengthening a multitude of aspects of life. Specifically, this course will focus on communication in the professional setting, and present material from multiple vantage points, including communicating with others in a variety of contexts, across situations, and with diverse populations. Upon completion, you will have a deeper understanding of both your own and others’ communication behaviors, and a toolbox of effective behaviors to enhance your experience in the workplace.
The Data Management/Analytics Undergraduate Capstone challenges students to demonstrate competencies supporting all BSDMDA program outcomes. Students will identify an organizational need, plan and develop a data analytics product to serve that need, and document the process in a project proposal and data project report.
Program consists of 39 courses
At WGU, we design our curriculum to be timely, relevant, and practical—all to ensure your degree is proof you really know your stuff.
Special requirements for this program
At the end of your program, you will complete a capstone project that represents the culmination of all your hard work—a research project applicable to the field of data analytics and management that aims to expand the body of knowledge in the profession.
According to a 2021 Harris Poll, just two years after graduation, WGU grads report earning $18,200 more per year, and that amount increases to $25,900 four years after graduation.
On Your Schedule
No class times, no assignment deadlines. You are in charge of your learning and schedule. You can move through your courses as quickly as you master the material, meaning you can graduate faster.
The data management and data analytics bachelor's degree at WGU is 100% online, which means it works wherever you are. You can do your coursework at night after working at your full-time job, on weekends, while you're traveling the world or on vacation—it's entirely up to you.
One important measure of a degree’s value is the reputation of the university where it was earned. When employers, industry leaders, and academic experts hold your alma mater in high esteem, you reap the benefits of that respect. WGU is a pioneer in reinventing higher education for the 21st century, and our quality has been recognized.
3rd Party Data Management Certifications Included
This combined data management and data analytics degree also includes multiple industry-recognized certifications from organizations such as CompTIA, Udacity, and CIW. You can “earn while you learn” when you choose a degree in data management and analytics from WGU—your valuable certs can start boosting your résumé before you even graduate. Udacity Nanodegree holders enjoy ongoing support from Udacity that includes employment placement, résumé support, networking and LinkedIn guidance, and more. Earning your Udacity Nanodegree as part of your program entitles you to all the benefits offered by Udacity— without adding any cost or time to your degree program.
- CIW Data Analyst
COST & TIME
An Affordable Online Data Management Degree
By charging per six-month term rather than per credit—and empowering students to accelerate through material they know well or learn quickly—WGU helps students control the ultimate cost of their degrees. The faster you complete your program, the less you pay for your degree.
A College Degree Within Reach
There is help available to make paying for school possible for you:
Designed for Professionals with Tech Talent, Competency-Based Education Puts You in the Driver’s Seat of Your Data Management and Analytics Degree
You’ve worked in tech for years. Your experience, skill, and hard work have gotten you this far, but the next step requires something you don't have: your degree. We believe your experience should count for something. You deserve a bachelor’s degree program that will take into account all the know-how you’ve gained over the years, allowing you to move through courses as quickly as you can prove you've mastered the material. No waiting for other students or the end of the semester. No sitting through classes you could teach. Just a smart, direct path to the degree your career needs and the respect you deserve.
Drive Decisions and Lead Teams with an Online Data Analytics Degree Program that Prepares You for Your Future
Nearly every transaction, whether it's social, commercial, medical, or academic, requires the expert management and in-depth analysis of big data. And with the continuing, exponential growth of data, the corresponding need for data managers and data analysts is also on the rise. Earning a degree and top industry certifications in data analytics will give you crucial skills and training to be ready for this exciting and lucrative career. You'll be able to help drive decisions and act as a linchpin for your organization with your skills and experience.
Our economy runs on data, and the amount of data we use is growing at an unprecedented rate. Every industry from advertising to zoology is going digital, and the big organizations need experts who can manage their big data. When you have completed your data management and analytics degree online, you will find that your skills as a data analyst are in high demand. The knowledge, techniques, and certifications you’ll earn as you complete your degree will provide you with all the tools necessary for a for a successful career in big data.
Return on Your Investment
A Data Management Degree Program Designed to Help You Excel
Some of the job titles a graduate of this data management and analytics bachelor’s degree program are qualified for include:
- Data Scientist
- Automation Architect
- SQL Query Builder
- R Programmer
- AI Trainer
- Tableau Report Developer
- QA Analyst
- Python Programmer
- Analytics Manager
- Data Analyst
- Database Administrator
WGU Grads Hold Positions With Top Employers
Data Management and Data Analytics Admissions Requirements
To be considered for enrollment into this bachelor's degree program, students must possess a high school diploma or its equivalent AND demonstrate program readiness through one of the following:
- Option 1: Submit transcripts documenting completion of previous IT coursework. IT coursework must be 300-level or higher.
- Option 2: Possess a bachelor’s or associate degree (A.A, A.S. or A.A.S. acceptable) from an accredited post-secondary institution.
- Option 3: Demonstrate at least two years of IT work experience through resume review.
- Option 4: Submit official records of completion of current and active IT certifications, some of which may provide transfer credit into various programs.
- Option 5: Submit high school transcripts with a minimum GPA of 2.75 GPA and a B grade or higher in a S.T.E.M. (Science, Technology, Engineering, and Mathematics) course. *Only advanced mathematics courses will satisfy this requirement.
NOTE: You do not need to take the ACT or SAT to be admitted to this program. Learn why we don't require these tests.
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FAQs about Data Management and Data Analytics
- General IT Program Questions
- Data Management and Analytics Questions
You should speak with an Enrollment Counselor. WGU can often provide advice or resources to help a prospective student fulfill enrollment prerequisites.
When you enroll in a WGU degree program, our goal is to see you through to graduation. Admission requirements are designed to increase your likelihood of success. Years of data and experience with the nontraditional students WGU serves have shown us how various types of academic and professional experience can be highly important in helping a student persist to graduation. Industry certifications are one of many ways a student can meet eligibility.
WGU has an obligation to our graduates—and their current and future employers—to ensure WGU alumni have mastered the most up-to-date, current competencies and skills needed in the workplace. Recency of certifications helps us ensure that students have demonstrated competency in skills as they are needed in today's working world.
As a full-time student, you will be required to maintain a minimum pace of 12 competency units (CUs) per term for undergraduate programs or 8 CUs per term for graduate programs. However, there is no maximum speed—once you complete a course, you move immediately to the next, and you complete a course not by waiting for the syllabus, the professor, or the rest of the class. You progress by learning the material and proving it—so you can move through your coursework at the speed of your own learning and experience.
Instructors are highly educated, experienced experts in the subject matter of a course. Unlike in a traditional university where going to class means listening to an instructor lecture while you take notes and try to learn in a group setting, WGU's Instructors provide one-on-one instruction and support when you need it—tailoring the instruction to your precise needs when you need it. Instructors also provide additional resources, lead topical discussions in online communities, and find countless other ways to bring a specific course to life for students.
The best data analytics course will entirely depend on what you are hoping to learn! When you pursue a degree in data analysis you will learn a wide variety of things, including:
- IT Leadership
- Data Governance
- Data Systems Administration
- Advanced Data Management
- Introduction to Data Science
- Data Wrangling
- Data Analysis with R
- Machine Learning
- Data Visualization
- Introduction to Programming in Python
- Scripting and Programming
- Web Development Foundations
A degree in data analytics is well worth the time and cost for students. When you earn a bachelor's degree in data analytics you gain valuable credentials and experience that can prepare you for a wide variety exciting careers. Earning a degree can help you earn more money, be prepared for a promotion or career move, and give you increased stability in your career.
On average data analysts earn more than $70,000 per year, and the industry is expected to grow 20% by the year 2029. Both of these factors point to strong salary levels and high stability in the career, making it a good choice for many.
Data science and data analytics as IT fields are expected to grow 15-20% in the next few years. These professions are in high demand, especially when compared to the national average for job growth which is about 5%. More industries and organizations are understanding the need for highly trained data analysts and scientists to help drive decision-making, contributing to the high growth of these professions.
A bachelor’s degree in data analytics and management will qualify you for a number of entry-level data analyst positions. These positions include data engineer, operations analyst, data analyst, analytics engineer, and digital marketing analyst. You will need strong analytical skills with competencies in areas including statistics, finance, math, computer science, and economics. A data analyst degree will give you the skills and expertise you need to excel and progress in your career in data analytics.
A data analytics degree may qualify you for the following jobs:
- Data engineer
- Operations analyst
- Data analyst
- Analytics engineer
- Digital marketing analyst
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