Big Data Skills – Opportunities and Threats
April 25, 2013 Leave a comment
Big data. There are few conversations in the IT community which do not start, address, or end on the topic. Some conversations are visionary in nature, some critical, and many considering the challenges we’ll need to overcome in the process of understanding how to deal with big data.
Definitions of big data almost parallel the 3 V’s of big data, which are velocity, volume, and variety. We may call it a byproduct of massive data growth, cheap technology, and our ability to save everything. We may address the enormous volumes of data generated by social media, smart grids, and other online transactions.
However we also need to compress those ideas into a form we can understand and use as a basis for our discussions. For simplicity, we’ll use Gartner’s definition that “big data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision-making, insight discovery and process optimization.”
Enhanced decision-making? Insight discovery? Process optimization? Outstanding opportunities to enhance our decision support process. Just corral all the data available to us, and voila, we’re competitive on a global scale.
One minor snag – we’ll need to recruit skilled technical and business staff with both the skills and business experience needed to effectively exploit the potential of big data, as well as establish value to business, government, and quality of life.
In a well-quoted study by the McKinsey Global Institute (MGI), data is presented supporting the idea big data to ultimately become a key factor in competition, and competitiveness across all public and private sectors. The study also states that just in the United States we will have a shortfall of nearly 190,000 skilled professionals in deep analytics, coders, and mathematical abilities.
The Australian Workspend Institute acknowledges there is a shortage of talent, and that shortage is getting worse. Stating that the Australian mining, oil, and gas industries have identified a shortfall of 100,000 skilled engineers, the “war for talent” is further running up the cost of labor for staff with deep analytical skills across-the-board.
Boston company NewVantage Partners published the results of an executive survey of leading Fortune 1000 companies adding only 2% of those listed companies felt they had no challenges finding talent and skilled resources needed to understand and exploit big data.
Is it really that important to be on top of big data?
A 29 March 2012 press release from the Executive Office of the President (US) unveiling the country’s “Big Data Research and Development Initiative” stated “by improving our ability to extract knowledge and insights from large and complex collections of digital data, the initiative promises to solve some of the nation’s most pressing problems.”
Perhaps crime? BBC Horizon’s aired a special on big data in early 2013, highlighting the efforts of Los Angeles Police Department’s (LAPD) use of big data and analytics in predicting crime. Collecting crime data from over 30 million records in LA, demographics, geospatial, and other historical data from both LA and around the world, LAPD uses analytics to predict down to 300sqft when and where a crime will likely occur. With uncanny, almost creepy results.
Health information? Climate change? Mining? Earthquakes? Planets which may support human life?
Given the amount of data available, data being created, and the ability of intelligent data scientists to create models of the data value, most believe those who can harvest big data will gain significant advantage.
So what do we do, give up on big data and focus on other activities?
In a recent Forbes article on big data author Ben Woo from Neuralytix wrote ”when it comes to big data, we believe if you’re not doing it, your competitors are!”
The United States still holds a significant advantage, leading the world in individuals with skill and experience in deep analytics. According to the MGI the US, China, India, and Russia lead the world in gross numbers of capable data scientists, while Poland and Romania are graduating the highest numbers of students skilled in deep analytics.
As noted, as the world continues to embrace the science of data, those skilled individuals will continue in demand. CIO Magazine notes that “CIOs are competing for workers with strong math skills, proficiency working with massive data bases, and emerging database technologies, in addition to workers with expertise in search, data, integration, and business knowledge.”
Those skills CIO believe are the most difficult to find and recruit include:
- Advanced analytics and predictive analysis skills
- Complex event processing skills
- Rule management skills
- Business intelligence (BI) skills
- Data integration skills
David Foote, Foote Partner’s Chief Research Officer writes that “many colleges and universities haven’t yet risen to the challenge of teaching the skills that are potentially needed for analytics jobs.
Industry may be rising to the need, partnering with universities to form the National Consortium for Data Science (NCDS). According to a paper done by the University of North Carolina Kenan-Flagler Business School (UNC), the agenda for NCDS is to better align the university programs with the needs of private sector (and government).
UNC further advises 4 steps human resources and talent management organizations can take to bridge skills and talent shortfalls in deep data and big data analytics include:
- Educating themselves about big data. If the organization does not understand big data at an operational level, it is unlikely they will be able to recruit skilled data scientists who do understand the concept.
- Educate managers and senior leaders about big data.
- Develop creative strategies to recruit and retain big data talent.
- Offer plans and solutions on how to build the talent in-house.
NOTE: As a particularly positive note for Southern California readers, California State University – Long Beach (Long Beach State ) was identified in UNC’s report as one of the few schools in the world with a strong , focused deep data analytics program.
While there is no immediate solution to the global shortfall in big data talent, we are finally awakening to the need. The academic community will need to consider, design, and implement curriculum and programs to acknowledge the need for graduates capable of dealing with big data. This means back to the basic of mathematics, statistics, analytics, and other disciplines which will graduate capable data scientists.
The Internet, computers, and ability to collect data has changed our world, and created many difficult challenges in our ability to understand the opportunities. Time to step up to the challenge.