Data and Information Management (DAIM)

90% of all data today was created in the last two years - that's 2.5 quintillion bytes of data per day." [1]

ENTERPRISE TECH: Bernard Marr. May 21, 2018

Think differently about data

As the volume of information continues to explode, so does the need for IT professionals who can maximize the value of information assets while getting the right data to the right people at the right time.

The MS in Data and Information Management is a deep dive into collecting, processing, managing, and protecting traditional data and big data. The program emphasizes hands-on learning working in teams with students, faculty, IT professionals, and even business executives. Our students apply emerging technology to solve challenging problems for our corporate partners. DAIM prepares graduates for leadership roles as data scientists, data engineers, data analysts, and other data management positions. 

There has recently been a steady increase in the demand for data engineers. With the accumulation of vast amounts of data by companies, there arises a need for a means to store and process it efficiently while maintaining its accuracy, consistency, and accessibility.

2022 DAIM Graduates
DAIM Class of 2022: Tracey Dudding, Nolan Ierardi, and Amanda Tolman presented their final capstone projects on April 26th, 2022 to complete the DAIM graduate program.

Master Emerging Technology

Project-based courses provide hands-on experience with industry-leading and cloud native tools like Spark, Databricks, Snowflake, and Tableau. Each student’s deep dive culminates with a capstone project to demonstrate the student’s skills. All projects are proposed by our corporate partners to ensure that DAIM develops the essential skills, knowledge, and experience most needed by industry.

By blending theory and practice, students master the latest technology and learn fundamental concepts and principles in the following areas:

  • Data architecture; data modeling and design; data storage

  • Data warehousing; data analytics and business intelligence 

  • Data integration and interoperability; data quality

  • Data governance; data security and privacy

The MS program educates graduates to the advanced level required to deliver increasingly complex data management solutions for successful and rewarding careers. Graduates will be proficient with tools and techniques for managing traditional and non-traditional data, as well as the latest technology and best practices to manage, process, and protect big data. Graduates will also be prepared to design, develop, and maintain high-performance, fault tolerant systems with 24/7 availability.


What you will learn

DAIM teaches students to collect, process, manage, and protect traditional, non-traditional, and big data.

Traditional data is well defined and structured, typically produced by operational systems like point of sale and inventory management.

Non-traditional data is unstructured data, or lacking a well-defined structure, like videos and images.

  • Big data is characterized by volume, velocity, variety, and veracity.
    • Volume: scale of data – too much data to store. A single jet engine generates more data in one day than Twitter.
    • Velocity: speed of generating and processing data – too much data to process. Machines generate data faster than people ever will. As the Internet of Things expands, data speeds will continue to accelerate.
    • Variety: diversity of data – including text, sensor data, photographs and videos. Sentiment analysis mines tweets and other social media to measure how people feel, which is often used to determine what products and services customers like and dislike.
    • Veracity: data quality and availability – more variety means greater uncertainty about the quality of that data and its availability.
  • Big data cannot be processed and managed with traditional methods:
    • Collecting: filter real-time data streams selecting the most valuable data to process and store.
    • Processing: integrate multiple data sources; clean, transform, and analyze data; to take action.
    • Managing: reliable, distributed storage of structured and unstructured data.
    • Protecting: processes and policies to ensure the integrity, privacy and security of information assets.  

DAIM students learn, apply and evaluate emerging technology to identify and understand the strengths and weaknesses of each. This in-depth knowledge enables DAIM graduates to design an optimal architecture for any task.


Students will complete courses totaling 30 credit hours in areas such as advanced database management, data warehousing, mining and reporting, algorithms and data structures, and much more. Courses blend theory and practice to teach traditional data management methods as well as the latest technology and techniques for managing and processing big data. Learn more about the DAIM curriculum here.

Goals and outcomes

A graduate of our program will be able to apply database and information management concepts to solve specific problems, critically evaluate emerging technology in data managing and processing, design, develop, maintain and evaluate high performance, fault tolerant data management systems, among many other skills. Learn more here.

Hands-on experience

The Applied Research Center (ARC) is an industry consortium enabling corporate partners to attract, develop, and retain IT talent. The ARTIS Lab is an advanced, high-tech collaborative workspace that brings together students, faculty, and corporate partners to explore emerging enterprise technology. The Carilion Suite provides flex space for our partner’s employees to work in the lab. Our mobile audio/visual unit supports remote participation from any location.

The lab, the suite, and the consortium enable students to apply their skills and knowledge to solve industry problems while developing an extensive professional network. This unique environment gives students the practical, hands-on experience they need to design and develop the next generation of information systems.

Students learn, apply and evaluate industry-leading tools and emerging technology to gain the in-depth knowledge and experience necessary to design an optimal architecture for any task. Students learn valuable soft skills working in a professional environment with faculty, industry practitioners, and business executives. Competitive funding is available through assistantships, internships, and scholarships. Contact Dr. Jeff Pittges for more information.

Corporate partners develop a customized workforce, stay abreast of the latest developments in data management, and address business challenges. Corporate employees gain leadership experience and expose our students to career opportunities. Employees typically learn as much as our students and they transfer their newly acquired skills and knowledge to their colleagues.

Application Requirements

To apply, applicants must have a Bachelor's degree in a STEM field and successfully complete the GRE. However, GRE requirements are waived for students enrolled in the accelerated program or those who have already obtained a Bachelor's degree in Computer Science from Radford University. For a comprehensive list of application requirements, please refer to the link provided here.

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