Big Data And Analytics Expertise: Beg, Borrow Or Steal?
Demand for big data and analytics experts is on the rise, but it will take years for the supply to catch up. Here's how to cope.
It's a good time to be a big data and analytics expert -- 18% of big data-focused companies in our InformationWeek 2012 State of IT Staffing Survey want to increase staff in this area by more than 30% in the next two years, but 53% say it'll be hard to find people with the required skills.
More Global CIO Insights
- Ovum Technology Analysis: Compelling Trends and Successful Strategies for Externalizing Your Enterprise Through APIs
- Do BYOD the Right Way
White PapersMore >>
People with experience in both areas are "going for crazy prices," says Brian Courtney, general manager of industrial data intelligence at GE Intelligent Platforms. "We have a lot of analytics talent on staff already, but getting high-end analysts with big data experience is that much harder."
The genealogy site Ancestry.com is another big data shop looking to hire. It recruits from the likes of Google, Yahoo and Microsoft to find people with experience running Hadoop clusters, designing high-scale search technologies and analyzing big data clickstreams. Insurance company UnitedHealth Group, headquartered just outside of Minneapolis, also needs more analytics and data management professionals. The health insurer hasn't experimented with Hadoop or NoSQL databases yet, but it's an early implementer of SAS High-Performance Analytics running on EMC's Greenplum Data Computing Appliance. It's working with in-database text mining to prepare for a future in which it will have to analyze text-rich electronic medical records for patient care trends.
With companies as diverse as industrial giants, Internet businesses and insurance companies all competing for the same scarce people, it's no wonder there's a talent gap. It's also clear that there's no single prescription for filling the positions available. Among respondents, 33% say they'll "do a mix of retraining and hiring/contracting." The second-largest group, 28%, will "mostly retrain staff and hire/contract a few people." The third-most-popular choice is to "hire or contract to fill needs," cited by 16%. The smallest group, 11%, will "retrain staff we already have."
We hate to dash the hopes of those counting on a lot of external hiring, but it's unlikely you'll fill the talent gap with recent graduates and people lured away from other companies. The good news? It's a good bet you won't have to beg existing employees -- particularly younger employees -- to line up for training opportunities. If you've attended a conference on Hadoop or NoSQL in the last year, you've undoubtedly seen the throngs of 20- and 30-something data geeks (and some 40- and 50-something geeks) packing into the keynotes and seminars.
Few companies are crawling with big data experts, but if you work for a large or sophisticated company, there's a good chance there are analytics experts on staff. They're often found in the research and development or finance departments, and some companies are pushing these groups to share the expertise.
If you're set on new hiring, consider a recent grad. With the rise of Internet commerce early in the last decade, followed by the publication of best-selling business books like Competing On Analytics and The Numerati, interest in big data analytics started taking off in the academic world about five years ago. The stock-in-trade at schools of mathematics, computer science and business was typically degrees in statistics, operations research, computer science and management science, respectively. But interest in big data has sparked new degree programs in analytics, machine learning and data science.
When big new 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," Spohrer says. If the 10-year pattern holds for big data analytics, a new wave of graduates is just starting to emerge and will reach a steady stream by 2018. Top schools include North Carolina State University, which has a well-known one-year Master of Analytics program that had extensive support from analytics vendor SAS. Others on Spohrer's list include the University of Ottawa, Northwestern University, DePaul University and the University of Connecticut. The latest addition to the list of schools supported by SAS is Louisiana State University, which just launched a 10-month degree program patterned after the one at North Carolina State.
What makes an analytics degree different from, say, a degree in statistics or computer science? At LSU, an analytics degree combines the computer science topics of data management and business intelligence with training in statistics, predictive analytics and operations research. There's also a focus on areas such as fraud detection, risk management, text mining and process improvement.
If poaching experienced employees from other IT shops is more your style, realize that it's not just a matter of offering more money. Top talent wants to know they'll be working with the latest technologies, have access to training and can collaborate with like-minded colleagues. The best big data analytics experts have a mix of business and data acumen. Keep all that in mind in your quest to hire or be hired.