To say that we live in the Age of Big Data is, for most, old news. Big data industries encompass every sector of the modern global economy. Data analytics drives innovation, operations, research, and decision-making in healthcare, finance, retail, transportation, social policy, and nearly every important industry.
However, the opportunity in data analytics is also a challenge. Wielding such a powerful and far-reaching tool requires principled expertise in its application. As the technology matures, so must its execution in the real world. Due to its ubiquity, Big Data in and of itself is no longer the competitive economic advantage it once was. The advantage is when the insights extracted from Big Data are applied successfully in the real world.
Let’s review three prominent big data industries and how they employ big data analytics in their operations, forecasting, and decision-making.
Healthcare Data Analytics
Perhaps nothing more readily illustrates the importance of analytics improving people’s lives than healthcare.
Since the outbreak of the COVID-19 pandemic in early 2020, data analytics in healthcare has received more attention than in any other sector. As tragic and challenging as the pandemic has been, we would be in a much harder place today without big data analytics.
Predictive analysis aids in tracking and forecasting disease transmissibility and spread. Analysis, machine learning, and AI helped drive the rapid development and distribution of effective, life-saving vaccines. The vast amount of data collected during this social, individual, and economic ordeal provides valuable lessons for mitigating the next health crisis.
The benefits of healthcare data analytics go beyond acute crisis. Some (though certainly not all) examples include:
- Electronic Health Records (EHR): EHRs enhance patient information accuracy and interoperability, increase efficiency, and improve quality of care.
- Population Health: The pandemic is a stark example of analytics in the service of population health outcomes, disease forecasting, and resource management. Population health data also improves patient engagement and informs behavioral change and risk profiles for preventative health.
- Health Insurance and Costs: With an increasing focus on value-based care, data analytics tracks intervention and care outcomes, costs, and inefficiencies. The data uncovers trends and relationships that help control costs and improve patient care.
Overall, managing the multi-layered complexity of the economics and delivery of quality healthcare requires Big Data and its attendant insights. If the key to human well-being is our good health, there is no more important application of big data analytics than healthcare.
Transportation Data Analytics
These days, autonomous vehicles may be the first thing coming to mind when considering transportation data analytics. Indeed, “driverless cars” are a cutting-edge example of what big data analytics makes possible in the transportation sector.
Even as gee-whiz autonomous technology slowly becomes more commonplace in many cities, data analytics plays an everyday–even prosaic–role in the transportation sector. Data is key for us getting where we need to go from finding a parking place to metering traffic congestion and, of course, telling us which way to go.
The trade-off in the complex transportation and shipping system is resilience. Big data, AI, analytics, and machine learning are also critical for the logistics and predictive forecasting that keep the global economy moving–and help untangle shipping and supply chain shocks when unexpected events distress the system.
Agriculture and Farming
Data analytics plays a progressively vital role in farming and agribusiness. The grand scope of history reveals that advances in agricultural technology are fundamental in human progress and social organization.
In a climate-stressed world with growing billions of mouths to feed, “smart” agricultural practices are essential. Data analytics is the key to unlocking resilient farming and sustainable agribusiness.
Farmers use “historical and real-time data to make informed decisions in their fields,” writes Kyle Plattner in IoTforAll. “Data collected through AI, IoT, and advanced robotics is vital for farmers to know what’s happening with each seed, each plant, and each machine.”
GPS-enabled precision agriculture allows farmers to assess soil conditions within meters. Data fed to a precision planter capable of processing multiple seed hybrids employ AI and IoT to calculate the optimized seed variety and spacing for every few meters of land.
With low-tech technology like no-till farming and planting cover crops, data analytics increases yield, restores soil, and reduces chemical inputs.
Big Data Industries Meeting Today’s Challenges
Data analytics is not the sole purview of data scientists. Data moves and shapes how society functions from the cornfield to the traffic light, doctor’s office, and everywhere in between. Neither is economics only a theoretical exercise. In all the cases we’ve examined, data analytics is inexorably tied to economics.
With Big Data, we uncover hidden relationships, trends, and possibilities. Data allows us to build models of reality. Applied economics is how we manifest those models into material outcomes in industry, government, and society.
Therefore, applied economics is a discipline combining economic and data science–the “tangible science of social organization.”
Master of Science in Applied Economics
“Economists do not have to be tied to what we think of as the traditional economist career,” says Dr. Aleksandar (Sasha) Tomic, Program Director of Master of Science in Applied Economics at Boston College’s Woods College of Advancing Studies. Applied economics is “thinking about how things fit together,” he says.
We have the analytical tools, theoretical foundation, practical expertise, and ethical underpinnings required to solve problems with applied economics. Students acquire the skills and tools in the program to assume leadership roles in business, science, and government.
The innovative program is built from the ground up with a student-centered, industry-aligned focus. All the instructors bring a wealth of experience and knowledge to the table, but what sets the program apart is its support and collegial approach. “We are unwaveringly student-focused in everything we do,” Dr. Tomic says. “The program’s success hinges on the success of each student.”
Students complete five core and five elective courses. The Master of Science in Applied Economics offers 26 elective courses allowing students to hone their knowledge and skills toward their interests and passion.
The five core courses include:
- Applied Microeconomic Theory
- Applied Macroeconomic Theory
- Data Analysis
- Ethics, Economics and Public Policy
Applied economics is the art and science of finding solutions to difficult challenges. Graduates emerge with the tools, knowledge, skills, and connections to pursue leadership careers as problem-solvers in a data-driven world.