Data Science and Analytics

The Demand

Data science and analytics have become vital to everything from understanding the spread of disease to curating museums.  Governmental, cultural, medical, and business organizations use newly available data and analytical tools to understand and attack challenges.

A 2011 report by the McKinsey Global Institute, Big Data: the Next Frontier for Innovation, Competition, and Productivity, noted that big data is growing at a rate of 40 percent each year, with broad application in virtually every sector, including scientific organizations and cultural institutions. Big data has the potential to add $300 billion of value to the nation’s health care industry alone.

Projections by Gartner, Inc., indicate that in less than 12 months, 4.4 million information technology jobs will be created globally. About 1.9 million of those jobs will be within the US, and big data has the potential to create three times that number of jobs outside of information technology (Gartner, 2014).

Despite this demand, the US faces a significant shortfall in the number of data scientists and “data-enabled” professionals.

The BHEF Approach

While there is considerable need for highly trained data scientists, there is an even greater societal need for the analytics-enabled professional who can marry a deep background in a particular field (e.g., the arts, agronomy, economics, finance, health, or business) with a strong understanding of analytics and visualization tools. Data-analytics-enabled individuals with discipline-specific expertise who can turn data into understanding will be increasingly critical to the ability of government, businesses, and nonprofits to implement data-driven decision making.

Most college and universities confine the opportunities to receive education in data science to the graduate level and upper-level undergraduate courses in engineering or computer science, inadvertently reducing the diversity of the pool of data-science-enabled professionals. Learning opportunities in data science will need to be integrated into courses in the broader undergraduate curriculum if for no other reason than to ensure a diverse data-science workforce.

BHEF develops and promotes evidence-based practices to design new programs and student experiences—for example, capstone projects or year-long, interdisciplinary team efforts—in data science and analytics for the non-STEM undergraduate population. Strategic partnerships between institutions of higher education and business and industry in developing these programs result in a significantly more diverse talent pool entering the data-science and analytics-enabled workforce.