Big Data is impacting many areas of science, engineering, and industry; from analyzing troves of weather data to modeling traffic patterns to processing millions of online customers, it is the enormous data which is creating new opportunities and challenges.
To tackle these challenges, one must have the training to store, manage, process and analyze data at these scales. But the challenges are beyond scale alone, the complexity of the data requires new powerful analytical techniques. Finally, it is crucial to have skills in communicating and interpreting the results of this analysis. A person trained in all of these skills is a big data scientist.
This emerging field – which addresses large sets of data too complex, diverse or rapidly changing for one computer to handle – affects everything from studying traffic patterns to managing sensitive information online. Big data is also big business – for example, using big data to improve efficiency and quality in the health care sector is estimated to be worth more than $300 billion each year.
“We’re seeing a revolution in the availability of data. It’s easy to collect information, but processing and analyzing large stores of data is becoming increasingly difficult. We are at the point where the traditional analytical tools for attacking this problem are breaking down,” says Jeff Phillips, assistant professor of computer science and coordinator of the new program. “Our program capitalizes on University of Utah’s strengths in computer science and big-data processing, and will provide students with the technical training needed to succeed in high-tech jobs in data analysis and management.”
Drawing on existing courses in computer science, the university’s new certificate program will provide graduate students and professional computer scientists with the skills needed to process, analyze and manage sets of large, complex data. The certificate consists of five courses (15 credit hours) in data mining, machine learning, database systems, visualization and advanced algorithms. These courses already are taught at the U, and will include options for distance education such as online video, internet-video office hours and classes late in the day.
Although use of big data is a national trend, the skills needed to manage big data are especially critical in Utah, where companies such as Adobe and Goldman Sachs, as well as the National Security Agency, store vast reserves of data. The program also will include training on ethical issues associated with data management and analysis.
The certificate will be coordinated through the university’s School of Computing and will officially begin in fall semester 2014.
To learn more about the data center engineering program, please visit: http://www.cs.utah.edu/bigdata/.
The UDCC Internship Program is designed to provide the intern an opportunity to work in Utah's regional data centers for extended rotational periods with multiple data centers fostering an understanding of real world data center operation in multiple settings. The build of the program enables the intern a chance to work in data centers supporting missions ranging from asset colocation and marketplace hosting to government and even intelligence services and markets ranging from regional to international. The internship program also offers rotations with groups that support data center operation such as equipment manufacturers and consulting services.
Rotations: The intern rotations are 3, 6, 9, and 12 month rotations or defined project rotations and may include attainment of a security clearance and rotations in secure federal facilities. Summer rotations are expected to be full time at 40 hours per week and academic year rotations are expected to be part-time up to 20 hours per week.
All students demonstratively seeking the Data Center Management Certificate are eligible for the UDCC Internship program.
The curriculum required for the Undergraduate Data Center Engineering Certificate prepares students to deal with the specific needs and challenges of the complex environments of modern data centers in government, industry, and academia. In particular, the program provides students with skills associated with facility planning, decision making supporting operations management, infrastructure design, and resource management for (large scale) data centers.
To earn a certificate students take 27 credit hours involving areas such as Computer Science, Electrical Engineering, and Mechanical Engineering. Students will choose two classes from each area plus management and capstone class on best practices in data center operations (new class). This program is designed to provide students with the broad foundational preparation needed for managing operations in modern data centers. This interdisciplinary combination of classes addresses the specific needs of this industry sector for a skilled workforce with knowledge in power and thermal engineering, computer science, general management, and best practices for managing large scale facilities.
Following the course outline, participating students will continue to connect with other students and professionals in this field, which will require students to develop individually and in small groups, understand and identify engineering knowledge leading them to a thorough understanding of the principles of large-scale data center management.
In addition to the capstone course, the program requires students to develop and deliver skills in the Computer Science, Electrical Engineering, Mechanical Engineering and Management fields. These are courses designed to promote this new knowledge at the proper beginning level needed for this certificate.
The central component of the Data Center Engineering program is a certificate that involves 8 classes in Computer Science, Electrical Engineering, Mechanical Engineering, and Management (two in each area). These classes are organized as follows:
OIS 5670 – Managing Service Operations (prerequisites waved):
Service companies constitute the largest and fastest-growing segment of the economies of the United States and many other countries. To successfully compete in this emerging service economy, it is critical for business managers to understand the managerial issues and problems unique to designing, producing, marketing and delivering services. This course aims to develop a better understanding of best practices in the service sector through analysis of leading-edge firms and the strategies they have employed to create and maintain competitive advantage. Topics include the design and delivery of breakthrough services, managing the service encounter, and the role of technology, in particular information technology, in changing the nature of the service delivered and/or the way in which the service is delivered. The course relies on the analysis of a number of case studies, and includes a project where the principles developed in the course are applied to a real service organization
CS 5030 – Current Data Center Operational Practices (capstone class):
This course will focus on the evolving design elements and the latest operational practices employed in modern, large-scale data centers for efficient management of electric power, computational and data load, and cooling. The course will include both seminars by professionals from design firms and local data centers and reports by students who have completed internships at these facilities. We will also tour several local data centers during the term and expose students to the latest green technologies adopted in Utah data centers. Enrollment is limited to those enrolled in the Data Center Engineering program with either senior or masters student standing.
Two classes in Mechanical Engineering (Thermal Systems and Design) (7 credits):
ME EN 3650 - Heat Transfer for non-majors (prerequisites waved)
Basic mechanisms of heat transfer, law of conservation of energy, conduction, convection, radiation, heat transfer with change of phase, heat exchangers.
One class chosen among the following three:
ME EN 5800 - Sustainable Energy Engineering:
Engineering of energy collection and production systems that satisfy long-term energy needs while minimizing damage to the earth's ecosystem. Conversion of chemical and nuclear fuels to produce work or electrical energy. Solar, wind, biomass, geothermal, co-generation and direct energy conversion. Conservation, seasonal underground energy storage, and hydrogen production technologies.
ME EN 5810 - Thermal System Design:
Design of steam-power plants, feed-water heater systems, pumping systems, compressor blades, turbine blades, and heat exchangers. Equation fitting and economic analysis as basis of design decisions. Optimization of thermal systems using Lagrange multipliers, search methods, dynamic programming, geometric programming, and linear programming. Probabilistic approaches to design.
ME EN 5820 - Thermal Environmental Engineering:
Principles of design of systems for heating and cooling of buildings. Heat-load calculations, psychometrics, thermodynamic systems, and solar-energy concepts.
Two classes in Computer Science (8 credits):
CS 3810 - Computer Organization:
Credit hours 4
An in-depth study of computer architecture and design, including topics such as RISC and CISC instruction set architectures, CPU organizations, pipelining, memory systems, input/output, and parallel machines. Emphasis is placed on performance measures and compilation issues
CS 4400 - Computer Systems:
Credit hours 4
Introduction to computer systems from a programmer's point of view. Machine level representations of programs, optimizing program performance, memory hierarchy, linking, exceptional control flow, measuring program performance, virtual memory, concurrent programming with threads, network programming
Two classes in Electrical and Computer Engineering for Power Engineering (6 credits):
ECE 2210 - Electrical and Computer Engineering for Non-majors:
Fundamentals of electrical and computer engineering topics for non-electrical and computer engineers. Covers fundamentals of dc and ac circuit theory, active semiconductor devices (diodes, transistors, amplifiers), 60 Hz-power circuits and equipment (2 and 3 phase circuits, transformers, motors), transducers and actuators, safety considerations.
ECE 3600 - Introduction to Electric Power Engineering:
Introduction to AC power generation, distribution, and use. Topics will include single-phase and 3-phase power, power factors and corrections, transformers, power distribution and the grid, generation plants, and some wiring and AC motors