In times of global economic crisis, there is an unstable situation in the labor market. Innovation is considered a savior in our current economic uncertainty, as nations shift their prominence in a worldwide marketplace where intellectual resources become increasingly important for the future development of the U.S.

The Big Data revolution opens new capabilities around analysis, research, and the study of both structured and unstructured data, unlocking an interesting and rapidly emerging market in data science.

“Within Big Data are opportunities to transform from being a market follower to a first-mover advantage,” said Bill Schmarzo, CTO inside EMC’s EIM and analytics division, who consults with many Big Data practitioners. Speaking of theses EMC services Big Data customers, Schmarzo said they are [gaining insights on the markets, products, customers and competitors that they can leverage to drive differentiation in their business.”

In recent months in the U.S. alone, large organizations, from staffing companies to universities, have seen a growing interest in a new professional class around data.  A curious mix of business expertise, analysis and information technology, this new title is underway in various vertical markets such as energy, commerce, healthcare and financial services. And if experts are right, this is just the beginning.

What is a Data Scientist?

In a world where data sets are exploding, companies try to understand how to extract the value of all the data they collect. This new science around data is made possible by the fact that the databases and analysis tools have been completely redesigned in recent years, which has greatly improved their performance and reduced memory demands that they required to function.

Data scientists are primarily capable of bridging the gap between raw data and analysis to make them accessible. The data can now be more effectively extracted, formulating and implementing quantitative analysis models in a proactive manner.

Scientists have to draw structured and unstructured data from various sources, including real-time communications, and try to understand them to add value to business.

“What makes a data scientist unique is his ability to use technology and hacker skills to solve actual real-world problems,” said Geoff Domoracki, founder of Dataweek.

The Rising Demand and Shifting Job Market

The big data industries are emerging to evaluate, access, analyze and use humongous volumes of data through scientific technology, and this will require a whole new army of workers on a global.

According to a McKinsey study, the U.S. alone would face a shortfall of 1, 92,000 data scientists against its requirement of 4, 90,000 by 2018. The demand will rise as enterprises today only use 5 percent of the data they create and store.

“A significant constraint on realizing value from Big Data will be a shortage of talent, particularly of people with deep expertise in statistics and machine learning, and the managers and analysts who know how to operate companies by using insights from Big Data,” the report said. “We project a need for 1.5 million additional managers and analysts in the United States who can ask the right questions and consume the results of the analysis of Big Data effectively.”

The report suggested that the rise of multimedia, social media and the Internet of Things will fuel exponential growth in data for the foreseeable future, and is estimated that data volume will grow 44 percent between 2009 and 2020.  The Internet of Things alone will act as an emergence of major data sources.  A recent Cisco report predicts that there are approximately 35 billion electronic devices that can connect to the Internet in today’s market.

Another report from EMC found that new technologies will increase the demand for data scientists.  More than half of the respondents in the report believe that demand will outpace supply.

In the U.S. alone, healthcare, retail, manufacturing and personal-location data will become a key basis of competition, underpinning new waves of productivity, growth and innovation.  The Healthcare industry by itself can create more than $300 billion in value every year in harnessing big data.  In a similar thread, personal-location data could capture $600 billion in consumer surplus.

Lack of Programs and Skills

The U.S. administration is getting more serious about shifting manual workforce back to the U.S. from outsourcing countries like India and China. But there is a lack of efforts when it comes to developing the brains needed to discover new possibilities and more importantly, turn them into actions.

Companies that try to handle large volumes of statistical silos of data are failing to understand the business and technology challenges. For example, the MBA programs in the U.S. today talk more about business concepts, such as product development and management, but are not able to analyze and interpret data.  On the flip side, mathematicians and statisticians do not have a deep understanding of the business.  But hopefully that’s beginning to change.

“IBM started a generation of Cobol programmers,” said Pat Gelsinger, president and chief operating officer of EMC Corp., referring to one of the first dominant programming languages. “Thirty years ago we didn’t have computer-science departments; now every quality school on the planet has a CS department. Now nobody has a data-science department; in 30 years every school on the planet will have one.”

According to experts, the presence of the master or doctoral degree does not affect the demand for specialists in the labor market. Increasing the attractiveness of the research work for young professionals who have received higher education is largely dependent on changes in attitudes towards science in U.S. society.  In this regard, the primary measure should be to increase government spending on the development of research and development.

In addition, several issues related to privacy, security, intellectual property, and even liability will need to be addressed to capture the full potential of big data.

How Big Programs are Changing the Way we Lead

Today, the US government agencies and private programs are recognizing the scientific, biomedical and engineering research communities are undergoing a profound transformation with the use of large-scale, diverse, and high-resolution data sets that allow for data-intensive decision-making.

National Science Foundation

The Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIGDATA) solicitation from the National Science Foundation has developed programs to advance the core scientific and technological means of managing,  analyzing, visualizing, and extracting useful information from large, diverse, distributed and heterogeneous data sets.

The program encourages the development of new data analytic tools and algorithms; facilitating scalable, accessible, and sustainable data infrastructure; increasing understanding of human and social processes and interactions; and promoting economic growth and improved health and quality of life.

Advanced Analytics at North Carolina State University

Institute Director of the Institute for Advanced Analytics at North Carolina State University, Dr. Michael Rappa trains students to be data scientists  including data analysts, is its ability to create a logic behind the data that lead to business decisions.

Rappa and his fellow professors have been refining their graduate program to educate scientific data. Rappa admits that the term ‘scientific data’ is much more attractive than its parts statesman and computer scientist.

“The scientific data should have an opening to solve business problems, not only be able to do some clever work of modeling. We educate students in a way that transcends disciplines,” notes Rappa.

This approach was adopted successfully, with 100 percent of participants placed in jobs prior to graduation. In fact, the program has recently expanded its annual enrollment of 40 to 80 to meet demand from public and private sectors as hundreds of companies visit the institute every year to recruit students.

Data Sciences Summer Institute of the University of Illinois

Eric Horn, director of education in the Data Sciences Summer Institute of the University of Illinois runs program for students and those in the Informatics Institute at Illinois Universidad are trained in various machine learning algorithms, natural language processing and intelligent search algorithms. They also learn how to apply these algorithms in numerous domains such as health services.

Workforce Opportunity Services from Dr. Art Langer

Seven years ago, Dr. Langer started Workforce Opportunity Services’ (WOS) training program that focused on high school students from economically challenged backgrounds. The program educates students to perform QA, application development and project management jobs.

To date, the program has successfully graduated over 200 students and also pays to them for their graduate program. The program has since been replicated at Rutgers University in Newark, NJ and in Akron, OH and El Paso, TX.

Coding is the New Literacy

Everyone ought to be able to read and write, but should everyone be able to program computers? The question is important as digital evolution is playing a central role in our daily lives today.

Penny Herscher, CEO of FirstRain, discussed how the evolution of software and big data is changing the way world is communicating today. At the recently concluded TEDx, she said texting, Facebook, Tumblr, TV, movies – all are constructed in software and teenagers spend more than 10 hours a day online interfacing through these digital channels.

The software code literacy movement is touching everyone: from illiterate women in India running micro businesses through a cellphone to CEOs and bankers, and students at a Palo Alto High School.

The movement of code literacy is gaining momentum and its success or failure will ultimately play a major role on our society and job market.

The scientific data project at PayPal

PayPal’s lead researcher Mok Oh is creating a team of scientists to study tens of petabytes of data generated by their customers and partners to predict buying patterns. Oh wants to mix carefully and is putting resources behind data behavior analysis to develop profiles and discover trends that will help attract new customers to PayPal and its partner ecosystem.

Contributors: Kristen Nicole