Big data is a hot topic that shows up somewhat regularly in all aspects of our lives. These days big data plays a role in nearly everything: the music we listen to, the GPS that guides us around new places, the healthcare system we are dependent upon, and so much more. Over 2,500 petabytes of data are collected daily and used to make our lives easier and more efficient.
There is no doubt that the world wouldn’t have advanced as rapidly as it has without the advent of big data processing. But what many of us fail to grasp fully is the type of work and educational background that is required for professionals developing big data tools to keep coming up with advances. Many of us might think that a creative mind and the spirit of a designer is all that is necessary, but what matters more than all of that is a background in mathematics.
Maths education is a critical component of the big data equation. It is used in nearly every aspect of the process, from big data tool design to data collection, to data analysis. Often the mathematical work is completed upfront so that the end product is easy to use for folks from any profession without much mathematical expertise. Given this information, it is imperative to encourage young students to understand the power of a maths background, especially as it relates to STEM education.
Math and Big Data
By definition, data science is a combination of statistics and computation to interpret data for higher-level decision-making. Big data is essentially data science on a large scale: it involves the use of powerful computers to take larger data sets and create actionable intelligence in a fraction of the time it would take a human workforce. Statistics is a critical part of the whole operation, and a thorough understanding of statistical formulas is key to success.
Another very important aspect of working successfully with big data is the ability to write and read lines of code. There are numerous computing languages out there, including Python, C++, Java, and Pearl. The core of these languages is derived from mathematical equations and logic-based thinking that is required to direct a computer. The basis of all big data and computation, in general, is also derived from mathematics.
This isn’t only helpful in understanding and creating technology; it can help us understand the natural world. Hundreds of years ago, an Italian mathematician named Fibonacci described a very important correlation between numbers and nature. He introduced a number sequence that occurs over and over again in nature, as well as many aspects of society, such as computer processing and things like trading strategies. This exemplifies the many applications of a maths education.
Growing Need for Data
Today, there is a rapidly growing need for more data in nearly every aspect of our lives. Because of this, businesses are clamoring to hire competent mathematicians who have an interest in coding and utilizing big data tools to build brand recognition, targeted marketing strategies, or trend analyses. Between 2012 and 2017, big data staff grew between 13 and 23 percent each year.
Companies are already struggling to fill the gap in employment opportunities and experienced professionals. One example of this is within the marketing industry. Companies are desperate to hire professionals that can help them manage and make sense of the big data they are constantly collecting related to customer preferences, buying habits, socioeconomic status, and more.
A problem that many of them are running into is the lack of qualified professionals with a solid statistical background and understanding. More and more frequently, there is a proliferation of supposed big data experts that tend to only have a good grasp of the basics. There is such a profound need for an influx of students studying mathematics at a young age.
Boosting Interest in Math Careers
It is clear that education in mathematics can open a number of doors when it comes to big data careers in nearly every industry. But what is not so clear is why there is such a profound lack of young people clamoring for these high-paying positions. Many believe this empty applicant pool can be attributed to a number of things including a failure to promote STEM educational opportunities, stigmas related to pursuing an interest in math, and the high academic achievement required to qualify.
A lack of interest in statistics and math is a problem starting at a young age with the all-too-common I’m bad at math attitude. This belief is often reinforced by social pressures and carries onward into college. Many undergraduate institutions don’t even offer basic statistical courses to students that are not directly pursuing mathematical degrees. For many, developing an understanding of the subject doesn’t begin until graduate-level coursework.
Many that are successful in the industry of big data do not stop their education at just a bachelor’s degree, either. Nearly 80 percent of those working the field have at least a master’s degree, and many of those have completed PhD level work. Obtaining the level of education required for the position may also be a factor in the limited number of qualified applicants for big data careers.
Big data is a growing industry that fuels many of the advancements made in all aspects of our lives. Mathematical education is a cornerstone of big data, which has encouraged a growth in the need for qualified professionals with a background in math. There are many reasons why there is a lack of young math professionals, but given the right educational outreach and support, many students will choose to pursue these careers.
