Library Data Science Degree Programs

School	Program	More Info
Syracuse University	Online MS in Library and Information Science ALA-accredited. Multiple professional pathways or specializations available. No GRE required to apply. Complete in as little as 18 months.	Website
University of Denver	Master of Library and Information Science (MLIS) ALA-Accredited, No GRE Required. Complete in as few as 21 months.	Website
St. John's University	Online M.S. in Library and Information Science ALA Accredited, 24 months to complete. 4 specializations and 2 certificate options.	Website

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Information takes many forms, both analog and electronic. In an increasingly digital world, more industries rely on the aggregation, analysis, and dissemination of accurate electronic information - specifically, data. Obtaining a Master's of Library and Information Sciences (MLIS)Masters MLIS, with a specialization in data analytics or data science, may place degree holders at the leading-edge of data-driven solutions.

Click to find featured online library science programs currently accepting applications for 2024.

Are there online MLIS programs in Data Analytics and Data Science?

Yes. To meet the information needs of diverse organizations, more library and information sciences programs offer specializations in data analytics and data science. What makes these programs unique is their interdisciplinary approach, pulling from the fields of communication, technology, information, and science. As many of these programs are grounded in foundational library and information science practice - the location, organization, synthesis, preservation, and evaluation of information - online MLIS degrees in data analytics and data science prepare information professionals to address data-driven challenges from this unique perspective.

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Top Online ALA-accredited Data Analytics and Data Science Programs

The American Library Association recognizes library and information science programs that are committed to maintaining a standard of quality and integrity for their students, faculty, and staff. Many ALA-accredited programs offer coursework in in-demand areas, including data analytics and data science.

While some programs may be completed on campus, many allow students to complete their degrees through online or hybrid courses. This is especially appealing for students interested in technology and the electronic delivery of information. All of the following programs have been accredited by the American Library Association and can be completed fully online. Click for the full review of the best MLIS ALA Accredited library science programs.

In-Depth Review of Top Online Library Data Science Degrees

University of Maryland - MLIS Intelligence & Analytics Specialization

UMD's 36 credit hour Master of Library and Information Science program is respected and nationally recognized. Students complete four foundational courses that introduce core concepts in the profession. Then, if desired, students may choose a specialization or focus area. Intelligence & Analytics is a specialization that prioritizes information privacy and security, intelligence, and research.

Information security is the focus of this specialization, with coursework covering a broad range of subjects. Recommended courses include Information Architecture, Open Source Intelligence, Information Ethics, and Project Management. These courses are designed to build on foundational concepts. In addition to completing 7 electives in the specialization, students are required to do either a field study experience or a thesis.

The average time to complete the degree is just over two years, and students have a maximum of five years to successfully finish the program. Online students also have the option to complete coursework on campus. Consideration for admission requires completion of an application, official transcripts, statement of purpose, three references, and a current resume or CV. Tuition is based on residency. Maryland residents can expect to pay $811.90 per hour, while non-residents pay $1,769.38 per credit hour.

University at Albany, SUNY - MSIS Data Analytics Concentration

This Master of Science in Information Science emphasizes both skills and real-world experience, with students building on coursework through hands-on applications. The degree program consists of 36 credit hours. Of these, 9 are devoted to core courses, 21 to concentration courses, 3 to research methods, and 3 to an internship. The degree has been designated as a STEM (science, technology, engineering, and mathematics) program.

Those interested in a career working directly with data, may choose the Data Analytics concentration. Required courses include Database Systems and Data Analysis, Predictive Modeling, and Analysis, Visualization, and Prediction in Analytics. Students may then choose an additional 12 credits in supporting courses. Additionally students complete a 150 hour internship.

Ambitious undergraduates may also consider the accelerated undergraduate/graduate option, allowing both programs to be completed in only five years. Admission requires transcripts, three letters of recommendation, and a statement of goals. The GRE may not be required for admission if certain minimum standards are met. Tuition and fees are based on residency status.

Kent State University - MLIS Applied Data Science Specialization

Kent State University offers an accredited and fully online program for future information professionals. The program requires 37 credit hours for completion, which includes core coursework and electives. Courses in the MLIS core include Information Organization, People in the Information Ecology, Information Institutions and Professions, Research and Assessment in LIS, and a Master's Portfolio.

The Applied Data Science pathway has been designed for those interested in solving real-world data problems at the application level. Course options in this pathway include Digital Technologies I-III, Database Fundamentals for Information Professionals, Data Science, and Semantic Analysis Methods. Students in this pathway may also take coursework in computer science and computational data science.

Priority application deadlines are established for the summer, fall, and spring semesters. The GRE is not required for admission consideration. An applicant to the program may be required to participate in a personal interview if the admissions committee feels information is not adequately covered in application materials. Approximate tuition for the program is $26,800. Financial aid, grants, scholarships, fellowships, and graduate assistantships are available for eligible students.

Rutgers - MI Data Science Concentration

Rutgers' School of Communication and Information boasts a high-ranking 36 credit program. This graduate degree program is people-centered and career-focused, with an emphasis on technology and data. The Data Science concentration in Rutgers' Master of Information program emphasizes preparation for careers in healthcare, finance, e-commerce, and research and analytics.

The focus of the concentration is on recognizing data-driven problems and developing analysis-based solutions. Required courses include Foundations in Data Science, Data Analytics for Information Professionals, Problems Solving with Data, and Database Design and Management. Students must also choose relevant electives, which might include Competitive Intelligence, Digital Curation, or Social Informatics.

When enrolled full-time the program can be completed in 1.5 to 2 years. Approximate tuition, excluding fees, is $36,252. Financial aid and scholarships are available for qualified students. Admission for the program is based on previous academic performance, professional work experience, letters of recommendation, a personal statement, and a resume or CV.

Are there Bachelor’s programs in Data Analytics and Data Science?

Yes. Universities with a School of Information or iSchool may offer undergraduate degrees in data analytics and/or data science. These bachelor programs typically require 120 to 130 credit hours for completion, and may be offered online, on campus, or a blend of the two. Graduates of these programs, like more general undergraduate degrees in library scienceBachelors BLS, gain the knowledge and skills to obtain entry-level positions in libraries, archives, museums, and other information centers. It is important to note that the American Library Association (ALA) Best MLIS ALA Accredited does not accredit undergraduate degree programs.

San Jose State University’s School of Information

San Jose State University’s School of Information offers a Bachelor of Science in Information Science and Data Analytics. This undergraduate degree program prepares graduates to meet the information needs of users in a variety of settings. Coursework covers three broad areas, including data, technology, and people. Lower level general education courses may be completed in-person or online, while upper level courses are available exclusively online. Learn more about SJSU at the California library science degrees page.

University of Illinois Urbana-Champaign’s School of Information Sciences

The University of Illinois Urbana-Champaign’s School of Information Sciences offers a 123 credit hour Bachelor of Science in Information Science + Data Science degree. Students in the program learn to collect, organize, analyze, and store data for diverse organizations. The interdisciplinary program merges information science, computer science, statistics, and mathematics. The program also includes a research or discovery experience. More info the University of Illinois can be found at the Illinois library science degrees page.

Are there Doctoral programs in Data Analytics and Data Science?

Yes. Doctoral programs in library and information sciences generally focus on research areas specific to the school and faculty. Some offer concentrations relevant to data analytics and data science, allowing post-graduate students to pursue relevant and dynamic research in areas of big data, analytics, visualization, and emerging technologies. Some courses may be completed online, though many require on campus participation. While these programs may be a part of an ALA-accredited school, the organization does not accredit doctoral programs.

University of North Texas Information Science PhD program

With an emphasis on graduate education and research, the University of North Texas Information Science PhD program prepares post-graduate students to engage with an ever-changing information society. Doctoral students work with faculty in a number of research areas and have the option to pursue a Data Science concentration. This program is offered jointly with the UNT Department of Information Technology and Decision Sciences and UNT Department of Computer Science and Engineering. Students complete coursework across four blocks, including Information Science, Research, Data Science, and electives. More info the University of Illinois can be found at the Texas library science degrees page.

Drexel University PhD in Information Science

Drexel University’s College of Computing & Informatics offers an interdisciplinary PhD in Information Science. Through a combination of coursework and original research, doctoral students are prepared for careers in policy, academia, and industry. In addition to Information Science and Human-centered Computing, Data Science is part of the foundational core. Some courses in this specialization include Machine Learning, Applied Database Technology, Information Visualization, Data Mining, and Concepts in Artificial Intelligence. To successfully complete the program, students must take a comprehensive exam, submit a dissertation proposal, and complete and defend the dissertation.

What can you do with a Data Analytics or Data Science degree?

Graduates with a degree in data analytics or data science are prepared to use data to uncover information and trends, and inform and support decisions. While some graduates may choose to seek employment in a library, archives, or museum, others may work in the private sector or government. Due to the broad nature of data and data user needs, a degree in data analytics or data science may open a wide variety of professional opportunities.

Typical Online Data Analytics and Data Science Curriculum

It is not uncommon to find data courses in MLIS programs that specifically tailor learning for information professionals and information centers. In addition to foundational LIS courses, these programs generally cover topics relevant to big data, analysis, visualization, and research. An emphasis may be placed on the data needs for specific information users, applications, or organizations.

Coursework will vary by school, but the classes below are an example of those that may be completed in a data analytics or data science specialization, concentration, or pathway.

• Foundations for Information Professionals – An introduction to the profession of library and information sciences. Coursework will cover the history, current trends, challenges, policy, and other relevant topics that have shaped the profession. Core concepts of the discipline form the foundation of course topics, with emphasis placed on DEIA (diversity, equity, inclusion, and accessibility), advocacy, and ethics.
• The Information Lifecycle – In this foundational course, students will investigate the lifecycle of information, including techniques for information creation, acquisition, organization, management, and preservation. This course focuses on applications across a wide range of professions and information centers, preparing students to engage with information in a number of ways. Topics include information systems, software, and infrastructures.
• Information Architecture – With a focus on electronic and web-based environments, this course presents the principles and strategies of information organization. Topics include digital resource description, metadata schemas, and data modeling techniques. Through readings, case studies, and discussions, students will gain a foundation in principles and practices. Hands-on activities include data collection and database management.
• Data Analytics – This course has been specifically designed for the information professional. Students will explore the necessary skills and knowledge for the creation of datasets, performance of analysis, and development of digital information resources. An emphasis is placed on creating connections between raw data and the needs of information users. Topics include methodologies for data curation, management, and mining.
• Information Ethics & the Law – This introductory course prepares students for the ethical use of information and understanding of laws relevant to information access and use. Students will apply a range of theories to contemporary issues in library and information sciences and other information-centered disciplines. Real-world legal and ethical issues will be discussed and analyzed. Special consideration is given to obstacles and challenges facing contemporary societies.
• Data Visualization – Through an investigation of theory and practice, this course provides an overview of topics relevant to the graphical and visual representation of data. Students will explore real-world case studies and develop solutions that apply established and emerging technologies. An emphasis is placed on visualization that explicitly aids understanding. Course topics may also include design principles, digital tools, and evaluation.
• Data for Problem Solving – This course introduces quantitative and computational analytics. Common methods and industry best practices are covered, including tools, strategies, and evaluation techniques. Through discussions and case studies, students will explore foundational concepts, technologies, and programming languages.
• Research Methods – With a focus on the research needs typical of contemporary information centers, this course introduces strategies and methods of conducting data-based research. Students explore methodologies and practices relevant to the social sciences. Topics include research planning, evaluation of literature, and quantitative analysis.
• Thesis – An option for the culminating experience is completion of a thesis. This is a substantial research project completed with the support of an approved faculty member. This option requires development of a research question, application of appropriate methodologies, and presentation of findings to a scholarly audience. The thesis option is a good choice for students who plan to pursue a doctoral degree or a career where research is central to job responsibilities.
• Internship or Field Experience – This culminating experience consists of a supervised practicum in a pre-approved information center (library, archive, museum, gallery, or other relevant organization). With an emphasis on experiential learning, students are expected to participate in work that aligns to both the program outcomes and the student’s personal and professional goals.

Where can you work with a MLIS degree in Data Analytics and Data Science?

As demand continues to grow for data-informed decisions, MLIS graduates with expertise in data analytics and data science may find unique opportunities in diverse professional fields. While opportunities certainly exist in traditional library settings, more information professionals are finding themselves working in government, the private sector, and non-profit organizations. Graduates with a data-focused degree who are curious and flexible are likely to find a good professional fit in a rewarding environment.

According to the U.S. Bureau of Labor Statistics, careers for librarians are expected to grow between 2022 and 2032 by 3%BLS Librarians. However, careers for data architects, database coordinators, and other similar roles are expected to grow by 8% Database Administrators. Even more promising, data scientists, analytics specialists, and visualization developers will continue to be in-demand, with a projected 35% employment growth Data Scientists.

Examples of employers seeking candidates with these skills are local, state, and federal agencies, universities and colleges, e-commerce businesses, healthcare and medical centers, software developers, banking and financial organizations, think tanks, and non-governmental organizations (NGOs).

Common job titles in Data Analytics and Data Science include:

• Business Informatics Librarian
• Data Integration Specialist
• Research Impact Librarian
• Data Management Specialist
• Research Information Analyst
• Business & Data Services Librarian
• Data Management Officer
• Digital Solutions Data Scientist
• Risk Assessor
• Data & Information Visualization Librarian
• Performance Measurement Manager
• Digital Scholarship Librarian
• Data Strategist
• Research Data Manager
• Web Analytics Director