Artis College of Science and Technology
- Davis College of Business and Education
- College of Education and Human Development
- College of Graduate Studies and Research
- Waldron College of Health and Human Services
- College of Humanities and Behavioral Sciences
- Artis College of Science and Technology
- College of Visual and Performing Arts
- Other Offices and Departments
- Medical Laboratory Science
- Center for Information Safety and Security
- Biomedical Science
- Chemistry Department
- Geospatial Science
- Pre-Health Advisory Committee
- Radford University Planetarium
- Selu Observatory
- MS in Data And Information Management
- Department of Information Technology
- Anthropological Sciences
- Biology Department
- Museum of the Earth Sciences
- Department of Physics
- GIS Center
- Mathematics and Statistics
- Forensic Science Institute
- Department Name
- REALISE Students
- Department Name
The Concentration in Database at Radford University
Information is power. As a result, ensuring the integrity, security, and availability of data is a critical task within organizations. The Database concentration educates students in all aspects of data management from database design to database administration to data warehousing and analysis. The concentration also provides an excellent foundation from which to pursue a career in the design and implementation of database management system (DMBS) software.
Talented database engineers are challenging to find which creates high demand and high salaries. Radford University offers the only undergraduate database program in the state of Virginia. Students who complete the database concentration work with Oracle, the industry leading database management system (DBMS), for at least three semesters. The Database concentration prepares students for careers as database developers, database administrators, and data analysts and data scientists.
Database developers fall into two categories: software engineers and data developers. Software engineers design and develop applications and systems including mobile apps, web apps, and any other kind of software. Most, if not all, business critical systems are information systems that operate on data. Consequently, database skills make software engineers far more valuable. Some database developers work entirely in the database modeling data and writing code that executes in the database management system.
Data developers are programmers who process data. Raw data is dirty and messy. Raw data is often filtered to remove the chaff much like pay dirt is filtered to separate out the gold. The important data must be cleaned and organized to produce valuable information assets. Clean data typically needs to be prepared for different applications like data mining and analytics.
Database administrators (DBA) manage the database system. Data is one of the most critical resources for any organization. The DBA’s top priority is to keep the database up and running to ensure the data is always available. Data must be protected from unauthorized use. The DBA designs and implements access controls to secure the data. DBAs install software, patches, and upgrades. They manage backup and recovery to ensure data is never lost and they tune performance to maximize throughput.
Data analysts and data scientists are the rock stars of Information Technology. They understand data from a business perspective and help people and organizations make better decisions.
Data analysts are typically embedded in a functional unit (e.g., marketing) to answer business questions with data. Analysts produce reports and dashboards, often applying data visualization techniques, enabling business users to identify problems, recognize opportunities, and increase performance. Analysts improve business intelligence by describing what is happening now.
Data scientists try to predict what is going to happen. They work with the data team applying machine learning and deep learning to develop predictive and prescriptive data models. Data scientists typically have strong math skills and they use tools like R, Python, and Scala.
Machine learning uses historical data to predict the future. For example, predict which customers are most likely to churn (choose another service provider), identify customers most likely to respond to a marketing campaign, and improve customer service (e.g., predict customer volume at a grocery store and staff accordingly). Predictive analytics requires people to make decisions. Prescriptive analytics recommends actions to take. Many recommendations are being automated to increase response rate by removing people from the loop. Self-driving cars analyze the environment and determine the best direction to take based on data.
College Core Courses Required
|ITEC 110||- Principles of Information Technology|
|ITEC 120||- Principles of Computer Science I|
|ITEC 220||- Principles of Computer Science II|
|ITEC 225||- Web Programming I|
|ITEC 345||- Introduction to Information Security|
|ITEC 490||- IT Professionalism
|ITEC 320||- Procedural Analysis and Design|
|ITEC 325||- Web Programming II|
|ITEC 340||- Database I|
|ITEC 441||- Database II|
|ITEC 442||- Data Warehousing, Data Mining, and Reporting|
|12 Credits in:||300 or 400 level ITEC courses
(Except ITEC 301, 400, 493, or 498)
|6 More Hours in:||-Any 300 level or above ITEC course
(except ITEC 301 or 400);
-MATH 152 or any 200 level
or above Math course;
-ASTR 111 or ASTR 112;
-any Biology (except BIOL 301 or BIOL 302);
-any Geology (except GEOL 110 or GEOL 205);
-any physics; or
Degree Core Courses Required
|ITEC 122||- Discrete Mathematics|
|ITEC 324||- Principles of Computer Science III|
|MATH 151||- Calculus and Analytical Geometry I|
For more information on this challenging but highly rewarding major contact: Dr. Arthur Carter
Department of Information Technology
Box 6993 Radford University
Radford, VA 24142