Data and Information Management (DAIM)

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 engineers, data architects, information managers, senior database administrators, and other data management positions. 

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Master Emerging Technology

Project-based courses provide hands-on experience with industry-leading tools like Splunk and cutting edge technology like Spark and Flink. 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 – including Hadoop, Spark, and Hive – and learn fundamental concepts and principles in the following areas:

  • Data architecture; data modeling and design; data storage
  • Data integration and interoperability; data quality
  • Data governance; data security and privacy
  • Data warehousing; data analytics and business intelligence 

The MS program educates graduates to the advanced level required to deliver increasingly complex data management solutions while preparing them for successful and rewarding careers. Graduates will be proficient with tools and techniques for managing 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.

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What you will learn

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

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

Big data, characterized by volume, velocity, and variety refers to data that cannot be processed and managed with traditional methods.

  • Volume: scale of data – too much data to store and process. A single jet engine generates more data in one day than Twitter.
  • Velocity: speed of generating and processing data – machines generate data faster than people. As the Internet of Things expands, data speeds will continue to accelerate. 
  • Variety: diversity of data – including text, sensor data, photographs, and videos. Sentitment analysis mines tweets and other social media to measure how people feel – often used to determine what products and services customers like and dislike.  
  • Collect: filter real-time data streams selecting the most valuable data to process and store.
  • Process: integrate multiple data sources; clean, transform, and analyze data; and take action.
  • Manage: reliable, distributed storage of structured and unstructured data
  • Protect: processes and policies to ensure the integrity, privacy, and security of information assets.

Volume and velocity require real-time, fault tolerant, on-demand, distributed systems. Variety requires unstructured data storage and processing.

As described in a recent exploratory guide, Apache provides over a dozen projects for managing and processing big data including Hadoop, Spark, Storm, Flume, Kafka, and Flink. Some of this technology is already considered old and many overlap significantly.

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.

Curriculum

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.

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.

 

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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.

Together, 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.

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