An industry-supported online school provides a good grounding in the science and application of very large datasets.
A virtual school, developed by a team of leading software and hardware companies, is providing readily accessible education in the use of large information datasets. The classes range from entry-level sessions on the essentials of big data for managers to practical instruction for veteran programmers who are accustomed to managing more traditional relational databases.
The mission of BigData University is to provide training and broaden the expertise of the big data community, explains Ben Connors, director of BigData University and worldwide head of alliances with Jaspersoft Incorporated, San Francisco. The uses of big data are expanding, whether for improving the health of children, facilitating the search for clean sources of energy or analyzing intelligence data from unmanned aerial vehicles. As a result, managers are realizing the potential that may be hidden within large information files whose size is measured by petabytes and exabytes, Connors explains.
One of the loftier goals for BigData University is to help fill the gap in the number of professionals who will be needed in the future to work in the realm of big data. Connors cites a recent McKinsey study that projects a need for between 140,000 and 190,000 workers in both the public and private sectors over the next five years. In the area of highly trained big data technicians, the same McKinsey study projects a shortfall of as many as 1.5 million workers who can help manage the cloud-based servers needed for big data. That need, Connors says, will be felt most especially in sectors such as financial services, information security, health care, environmental research and energy. “It’s really a broad range of areas in which big data will be increasingly used, and we’ll need people in all those areas to leverage it,” he adds.
To date, nearly 50,000 students have registered and completed courses through BigData University. The classes all are online and are offered either for free or for a nominal fee. Students receive the content of BigData University through on-demand video lectures and online lab exercises. Currently there is no opportunity to ask questions of instructors or other students.
Course offerings range from entry-level classes in Hadoop, an application used to run big data analysis across cloud-based distributed computing environments; Standard Query Language (SQL); Database 2 (DB2); text analytics; Hadoop-reporting and analysis; query languages; Java fundamentals; and more specialized instruction in running cloud-based big data applications. One of the most recent additions to BigData University’s curriculum is a class focusing on big data analytics for business-specific applications, titled, “Hadoop Reporting and Analysis.”
“The class is designed to help managers derive useful insights, including security insights,” from big data applications in such areas as retail, marketing, big finance and other realms, Connors explains.
Classes are designed by participating companies to meet specific needs based on the real-world experience of their big-data customers, using a model for online classes originally developed by IBM. For example, Connor says, Jaspersoft offers four classes on topics focusing on Hadoop reporting and analysis.
The online school does not offer traditional degrees, but BigData University provides industry-recognized certification for those who complete its classes, Connors says. “There are fairly rigorous exams and proof-of-comprehension tests,” he adds, explaining that these are designed to demonstrate practical understanding of the class topics.
“We provide all the software, available for free download, and a cloud-based environment for students to get hands-on experience in the big data product.” Instructors are recognized experts, and all have regular jobs in which they either manage or operate big data within their employers’ big data environments. “Our faculty [members] come from the working ranks of big data practitioners,” he explains. The student body is “global in nature” and ranges from high school and college students to industry professionals. In general, Connors estimates, the average student might take roughly one week, working at his or her own pace, to complete one course, and could run through all of BigData University’s offerings in about six months.
While there is no required reading for BigData University classes, Connors says that some publications are made available to students for offline reference in relation to class work. Books such as Hadoop for Dummies, intended as an entry-level primer for the big data application, are among the manuals offered either for free or for a nominal fee to students.
BigData University began as IBM’s DB2 University, which was started in 2006 to provide online instruction to information technology professionals managing its relational database installations, Connors says. In summer 2012, IBM joined forces with Jaspersoft and other firms to expand the scope of DB2 University into the realm of big data. Jaspersoft is one of a number of companies that not only provides financial and technical support for BigData University, but also lends the expertise of its own employees to serve as administrators and instructors for the classes offered. Other partner companies involved in BigData University include IBM, Google, Amazon, Hortonworks, Cloudera and Treasure Data.
“We’re all believers in big data, and we believe there’s lots of value to be had, lots of potential in big data; and the more people who can use and understand big data, the better for all of us,” Connors adds.
More traditional academic institutions have taken note of the need and interest in advanced education in the area of big data. Last August, North Carolina State University became one of the first such schools to launch a Master of Science degree in analytics, to be offered through its four-year-old Institute for Advanced Analytics. Other institutions of higher education offering programs or advanced classes in big data topics include Stanford, the Massachusetts Institute of Technology, Berkeley, Harvard and Carnegie Mellon University.