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Data Management // Big Data Analytics
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Doug Henschen
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How To Fill Big Data Talent Gaps Fast

Consider training current employees or recruiting from our list of analytics master's degree programs.

 Big Data Analytics Masters Degrees: 20 Top Programs
Big Data Analytics Masters Degrees: 20 Top Programs
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Stop sweating the much-hyped big data skills gap and start exploring training and recruiting options.

Experts are trained, not born. One question you need to answer is whether you're looking for technical expertise or data expertise. Technical expertise is what's needed to bring NoSQL databases or Hadoop clusters into production. Data expertise is what's needed to take advantage of data mining, text mining, forecasting and machine learning techniques. Either way, let's start with the assumption that nurturing talent from within your current staff is the first and best option.

Our 2012 Big Data and Analytics Staffing Survey shows that most companies plan to do a mix of retraining, hiring and outsourcing to fill their talent gaps. But getting new salaries approved, working with recruiters, and interviewing and onboarding candidates is a time-consuming process. What's more, professionals on staff presumably have a good handle on your business, your data sources, your current analyses and most likely, what you're hoping to get out of big data and advanced analyses.

If it's technical expertise you lack, trust that your existing DBAs, database developers and data-warehousing pros can learn new tricks. Moving from a conventional database to a massively parallel processing (MPP) database platform, for example, is not a huge leap for your talented DBA, and the right person will be energized by the new challenge.

[ Want more on big data analytics staffing options? Read Big Data And Analytics Expertise: Beg, Borrow Or Steal? ]

Vendors invariably have low-cost training and certification options. Hewlett-Packard, for example, just announced course modules and certification exams around its MPP-based HP Vertica Analytics Platform. The introductory course is delivered over three days in HP ExpertOne classrooms around the globe. There is also an option for a virtual training online, which is delivered over four days. "It's technical product training on how to set up the software and get the most out of it, and it's geared to everybody from DBAs to data scientists," says HP's Chris Selland, VP of marketing.

Big data that's marked by data variety and extreme volume is mostly being handled on new platforms such as Apache Hadoop and NoSQL databases. Lots of companies without prior experience are getting Hadoop clusters into production in as little as five months, according to John Schroeder, CEO of MapR, a Hadoop software, support and training provider. "There's a scramble for talent right now because there are more projects than people, but the number of people trained in Hadoop is growing dramatically versus what we saw in 2010 and 2011," Schroeder says.

MapR and its competitors, Cloudera and Hortonworks, offer plenty of training courses. In MapR's case, they're typically two- to three-day MapR Academy video, online and classroom courses on topics including fundamentals of cluster administration; hands-on Hive, Pig and MapReduce training; and HBase programming. Cloudera University offers online and classroom courses globally while Hortonworks University offers classroom courses in major cities and, with six or more participants, on-premises at company locations.

The assumption with these training options is that you have competent system admin and developer types who can pick up on new technologies that don't have the familiar feel of SQL and relational databases. In the case of more advanced data-analysis-oriented courses, such as "Introduction to Data Science -- Building Recommender Systems" (offered by Cloudera University), the target audience is "software engineers, data analysts and statisticians with basic Hadoop knowledge and proficiency."

If your data-management team isn't up on advanced analytics topics like data mining, text mining and forecasting, you might consider recruiting from one of these top analytics master's degree programs. The shortest of these programs can be completed in 10 months, but that's full-time, so it's probably not appropriate for a current employee, unless they can take a sabbatical. There are part-time and online options that take about two years at a minimum.

We developed our master's degree compendium mostly as a resource for would-be students, but if you're in a hurry to fill a talent gap, look to these programs as a recruiting resource. The advantage of dealing with masters programs is that most students will have three or more years of business experience. Most schools will be only too happy to welcome new employers into their recruiting programs, particularly if they're larger firms that have a steady demand for new employees.

Some schools even do joint research with sponsoring companies, turning professors and teams of grad students loose on real-world business challenges. That's the case at North Carolina State University's Institute for Advanced Analytics and at MIT's Center For Digital Research. Look for research centers or institutes affiliated with analytics or big data degree programs.

The bottom line is that there are plenty of options other than hand wringing and high-priced head hunters. If you're looking for very senior people, the task will undoubtedly be harder. But before you buy into the "I can't find talent" hysteria, determine your needs, size up the training options and strike up a relationship with a local university.

Tech spending is looking up, but IT must focus more on customers and less on internal systems. Also in the all-digital Outlook 2013 issue of InformationWeek: Five painless rules for encryption. (Free registration required.)

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User Rank: Apprentice
1/11/2013 | 4:54:57 PM
re: How To Fill Big Data Talent Gaps Fast
Another option for training is EMC's Data Science & Big Data Analytics course, a self paced Video ILT. The course includes six modules with self-assessments on Introduction to Big Data Analytics, Data Analytics Lifecycle, Review of Basic Data Analytic Methods Using R, Advanced Analytics G«Ű Theory And Methods, Advanced Analytics - Technologies and Tools, The Endgame, or Putting it All Together. This training is available from Amazon here:

Kate Hutchinson
EMC Education Services

User Rank: Strategist
1/11/2013 | 12:25:46 AM
re: How To Fill Big Data Talent Gaps Fast
Companies can't have too many people trained in big data handling and analysis. Many different parts of the company will need to use it, including the IT staff, which if we're not careful, will end up in the position of the cobbler's children -- so busy supplying big data that it doesn't get to use it.. Charlie Babcock, InformationWeek
Heather Vallis
Heather Vallis,
User Rank: Apprentice
1/9/2013 | 9:14:38 PM
re: How To Fill Big Data Talent Gaps Fast
According to our 2012 Big Data and Analytics Staffing Survey, even though 81% of those citing big data/analytics as one of the top two areas of growth over the next year say they already employ people with skills specific to this area, 40% predict they'll increase staff by 11% or more over the next two years; of that, 18% foresee an increase of greater than 30%. This, coupled with companies relying on some degree of retraining to meet their needs, spells opportunity for qualified, internal staff to move into a new, and in-demand, role.

Heather Vallis
Managing Editor, Research
Eddie R.
Eddie R.,
User Rank: Apprentice
1/9/2013 | 7:58:06 PM
re: How To Fill Big Data Talent Gaps Fast
It's interesting to see this panic for new talent when there's actually quite a lot of talent out there already familiar with and working with Big Data. I agree a lot of the gap can be filled with training/retraining programs, and the availability of online courses like Cloudera will certainly help.

In college, I remember a professor sharing a quote: G«£We are currently preparing students for jobs that donG«÷t yet exist,using technologies that havenG«÷t been invented, in order to solve problems we donG«÷t even know are problems yet.G«•
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