53% of big data-focused companies say analytics experts will be tough to find for the next two years. Here's how IT leaders plan to train, borrow, or steal talent--and what job seekers should know.
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Tip 5: Plug Into College And University Programs When big technology waves come along, as we've seen in the last five years with big data analytics, it takes about 10 years to train the next generation on the new skills that are needed, according to Jim Spohrer, IBM's director of global university programs. "We're in one of those 10-year cycles right now where we're shifting to create the next generation of graduates," he says.
Thus a new wave of graduates is just starting to emerge and will reach a steady stream by 2018. Spohrer tracks IBM's work with various colleges and universities, including financial support, research grants, software and technology donations, and recruiting. Among the institutions on Spohrer's short list of top analytics schools are North Carolina State University (NCSU), the University of Ottawa, Northwestern University, DePaul University and the University of Connecticut. At SAS, Jerry Oglesby, senior director of global academic programs, also cites NCSU and Northwestern as leaders, but he also lists Louisiana State University, Oklahoma State, Texas A&M, Texas Tech, California State University at Long Beach and the University of Alabama.
Genealogy website Ancestry.com needs big data scientists who can work with Hadoop and write their own algorithms. To find employees who are hip to R statistical programming and MapReduce, the company is working with schools that have introduced course work or degree programs in machine learning. Scott Sorensen, senior VP of engineering, says institutions including Carnegie Mellon, California Polytechnic State University in San Luis Obispo and the University of California at Berkeley are among many that have stepped up their machine-learning programs.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
InformationWeek Must Reads Oct. 21, 2014InformationWeek's new Must Reads is a compendium of our best recent coverage of digital strategy. Learn why you should learn to embrace DevOps, how to avoid roadblocks for digital projects, what the five steps to API management are, and more.