Have You Considered These Careers In Big Data Analytics?

The big data market is booming. IDC forecasts that companies providing big data services and infrastructure will generate over $150 billion in revenue by 2018, and are expected to grow at a compound annual growth rate (CAGR) of 23.1 percent from 2014 to 2019. Revenue generated by Hadoop, the open-source software framework that has become almost synonymous with big data, is predicted to grow at 58.2% CAGR between 2013 and 2020.

According to a list compiled by the job site Glassdoor, half of the top 10 jobs in 2017 were related to analytics, big data, and data science:

TitleJob ScoreJob SatisfactionMedian Base Salary
Data Scientist4.84.4$110,000
DevOps Engineer4.74.2$110,000
Data Engineer4.74.2$106,000
Analytics Manager4.64.1$112,000
Database Administrator4.53.8$93,000

The LinkedIn 2017 U.S. Emerging Jobs Report echoes the popularity of jobs in big data:

  • Machine learning engineers, data scientists, and big data engineers rank among the top emerging jobs on LinkedIn.
  • There are 5.5 times more big data developers today than there were five years ago.

According to Dataconomy, most data scientists — 92 percent — have an advanced degree. Only 8 percent have a bachelor’s degree; 44 percent have a master’s degree, and 48 percent have a Ph.D.

Key capabilities of a data scientist

When we talk about the basics of subject matter, we usually refer to ABCs. With big data, however, it’s the 3Vs — volume, variety, and velocity — that are its defining properties. Volume refers to the amount of data, variety refers to the types of data, and velocity to the speed of data processing.

In addition to understanding these properties, those dealing with big data must possess:

  • An ability to look beyond the numbers — data scientists must understand that data has meaning
  • An understanding of the problem at hand and how the data can be used to solve it
  • An understanding of the infrastructure what’s needed before you can perform the analysis

Industry news website KDNuggets explores five career paths in big data, and what distinguishes each:

1. Data management professional: This IT role, similar to a database administrator, manages data and the infrastructure that supports it.

2. Data engineer: This job deals with designing and implementing the data infrastructure.

3. Business analyst: To glean insights from the data, this position requires interaction with (or querying of) databases and big data frameworks.

4. Machine learning researcher/practitioner: Statistics and programming are essential skills for this role, which involves crafting and using predictive and correlative tools used to leverage data.

5. Data scientist/data-oriented professional: This role uses data visualization, focusing on the data and the insights it can provide, regardless of what technologies or tools are needed.

No matter which path you choose, you can take comfort in the fact that big data as a whole is growing. While all industries will continue to see an uptick in big data jobs, Forbes has identified the top five industries hiring people with big data skills: insurance and financial services, scientific and technical services, IT, manufacturing, finance, and retail. Following is a closer look at these industries and how they are reaping the benefits of big data:

Insurance and financial services

The insurance and finance industries stand to benefit greatly from big data. For example, many insurers use big data to detect and prevent insurance fraud –  according to the Insurance Information Institute, fraud is responsible for 10 percent of property-casualty insurance industry losses each year, totaling $32 billion.

According to Investopedia, The New York Stock Exchange captures 1 terabyte of information during each day. That’s a lot of data. All of that data can be analyzed to attempt to anticipate future stock performance.

The finance industry also faces ever-changing regulatory and compliance requirements. This places greater emphasis on governance and risk reporting, calling for in-depth analysis at the organizational level.


As of 2014, all public and private healthcare providers – and other eligible professionals – are required to adopt and demonstrate “meaningful use” of electronic medical records (EMR) in order to maintain their Medicaid and Medicare reimbursement levels.

As a result, over the past five years, electronic health records (EHRs) have been widely implemented in the U.S., giving health care systems access to vast amounts of data that can be used to improve patient outcomes and hospital profitability.

As another example, big data is also playing a key role in research and development. Big data links real-world clinical, genomic, and lifestyle data, helping researchers identify new disease pathways and improve the drug discovery process. Big data also can help determine which patients may benefit most from a drug and, therefore, be included in clinical trials.

Technical services/IT

Technology companies must continually innovate in order to stay in the game.

Like any sector, tech companies can use big data to streamline and automate business processes, optimize the workforce, increase efficiency, improve productivity and, ultimately, boost the bottom line.


Whether it’s an e-commerce site, a brick-and-mortar store, a mall kiosk or a pop-up store, retailers are facing increased competition. Retailers destined for success are those that not only embrace big data, but use it to their advantage.

Retailers collect data from a variety of sources, including receipts, customer loyalty cards, point of sale (POS) scanners, RFID technology, inventory, social media, and local demographics data, to name a few.

And they use that data in numerous ways: to optimize staffing and scheduling, plan events, reduce fraud, merchandise products, and more.

Methods for capturing big data are continuously evolving. Drones, for instance, are one of the latest ways to collect data on a large scale. This data can be applied to areas from weather to traffic to disaster forecasting.

Those considering a career in big data should be reminded that facts and figures are no substitute for human interaction. In today’s mobile and digital society, with telecommuting becoming more widely accepted, people are increasingly craving “face time.” While valuable insights can be derived from big data, businesses that communicate consistently with their customers will, in the end, be exceedingly successful. Companies that combine qualitative feedback from their customers, along with quantitative data analysis, will outpace their competitors.

The beauty of a degree specializing in big data is that you can use it in virtually any industry. The concepts you master are applicable across multiple industries.

If you are looking to advance your career and better utilize big data, consider the Wake Forest online Master of Science in Business Analytics (MSBA). The MSBA enables working professionals to develop deep, quantitative capabilities and technical expertise to create business and social value, with marketable skills required by today’s top employers.