Google, Facebook and Amazon are reinventing the way we live. What do they all have in common, aside from being the world’s most valuable internet brands? These companies are leaders in big data. Oil and pharmaceutical companies may look pretty small in the coming years by comparison.
What Is Big Data?
Big data is not an industry, but a predominant means by which all industries — from healthcare and manufacturing to entertainment and fashion — are now deriving value. Even the public sector is increasingly reliant on big data. As vital to our economy as it is, big data is a misunderstood concept that would fascinate many people if they properly understood it.
For now, think of big data output as vast numbers of predictive models used by organizations in pursuit of business goals, including reducing labor costs and improving the customer experience. The more innovatively organizations use big data, the more they increase operating margins and become market leaders. Within organizations pioneering the applications, who are the wizards behind the curtains? Data scientists.
Companies are capturing ever-expanding, massive volumes of data from consumers’ online and offline activities, social media, multimedia, and the Internet of Things. With today’s constant connectivity driven by mobile technology, nearly every consumer action, from driving to the grocery store to tweeting about an election, generates valuable data. At the same time, data storage is becoming increasingly cheap, enabling companies to store more and do more with the data they store. The data is amassing exponentially, but few people have the skills to organize, extrapolate and monetize it.
What Could Be Accomplished with More Data Scientists?
The McKinsey Global Institute (MGI) has studied the applications of big data extensively. To illuminate its potential impact, MGI offers these examples:
- A retailer using big data could increase operating margins by 60 percent or more.
- If U.S. healthcare harnesses big data efficiently, the sector could create $300 billion in value every year and would reduce our nation’s healthcare expenditures by 8 percent.
- In the developing economies of Europe, governments could save more than $149 billion in operational efficiency improvements alone.
- Users of services enabled by personal location data could capture $600 billion in consumer surplus.
Forrester analyst Mike Gualtieri was just as optimistic about the future of data science. In a Datanami webinar, he outlined a vision that should inspire anyone with left- and right-brain aptitudes to consider a career in data science:
“…the future of data science will hinge on advanced analytics — specifically using predictive analytics and real-time analytics in pursuit of business goals, such as improving the customer experience, improving products and services, and reducing costs and churn.”
“…the tools are going to de-emphasize the mechanics of doing machine learning. So the data scientists are going to be more creative about the types of models they create, freeing them up to have more time for curiosity to discover new things that may be of value.”
Quantifying the Supply Shortage
The need to harness all of this data is driving demand for data scientists at a pace that university graduate programs have been slow to meet. Data scientists and business data analysts are people with analytical minds who combine business expertise with math, science and computer science acumen. There is a significant and persistent shortage of this talent, according to several research groups:
- In 2011, McKinsey predicted a shortage of 140,000 to 190,000 data scientists and related positions by 2017, resulting in a demand 60 percent greater than supply.
- In 2012, Gartner predicted a national shortage of 100,000 data scientists by 2020.
- In 2014, Accenture found more than 90 percent of clients planned to hire data scientists, but more than 40 percent cited a talent shortage as an obstacle.
- A 2016 CrowdFlower Data Science Report revealed that 83 percent of survey respondents cited a shortage, an increase from 79 percent in 2015.
What Employers Need
Employers are hiring people with varied educational and professional backgrounds for roles in data science. The right talent may come from dedicated data science programs, as well as MBA or even Ph.D. programs. Organizations like Cisco are working with universities to develop distance learning education and online certification programs to meet their specific needs. Universities are picking up the slack too, with MBA and other post-graduate programs that offer a focus on data science and analytics.
Generally, employers look for a combination of training and skills, not necessarily a specific degree or certification. Because the demand is so high and much of the work is collaborative, organizations want to assemble teams with diverse and complementary skill sets. The potential for generating new ideas is plausibly higher in such scenarios, in which a Ph.D. in experimental physics can brainstorm with an MBA with a concentration in business analytics.
Meet the Demand by Obtaining a Focused MBA
Florida International University is rated in the “25 Best Value Online MBA Programs” by Business MBAs and ranked among the top 50 MBA programs by Financial Times. The Corporate Master of Business Administration Online with an emphasis on Business Analytics prepares you to meet the growing need for data analysis in business environments.
In addition to core MBA courses, the program focuses on data storage, databases, reporting and analysis. The degree can be completed by working professionals in as few as 18 months. Among all of the available post-graduate options, this program offers one of the most time-efficient and cost-effective entrees into the rewarding field of data science.
Learn more about the FIU online MBA program with a specialization in Business Analytics.
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