At heart, analytics is all about solving problems. The problems just happen to be on a much larger scale than what many of us are used to – effecting entire businesses, along with the staff and customers that they serve. The ability to think analytically and approach problems in the right way is a skill that’s always useful, not just in the professional world, but in everyday life as well.
This is the obvious benefit to learning data analytics, and the one most often focused on by students in higher education. Put simply, data analysts are valuable, and with a looming skills shortage on the horizon as more and more businesses and sectors start working with big data, this value is only going to increase.
Aside from the financial benefits that the high demand for data analytics can provide graduates, the big data boom has also meant that there are all sorts of new opportunities cropping up for talented employees. This could be working in a variety of different industries such as aviation or government, or simply having the opportunity to travel the world.
With the abundance of data available at our fingertips today, the opportunity to leverage insight from that data has never been greater. This will have a few impacts but primarily the value of data analysts will go up, creating even better job opportunities and career progression options.
One of the earliest adopters is the financial sector. Data analytics has an important role in the banking and finance industries, used to predict market trends and assess risk. Credit scores are an example of data analytics that affects everyone. These scores use many data points to determine lending risk. Data analytics is also used to detect and prevent fraud to improve efficiency and reduce risk for financial institutions.
The use of data analytics goes beyond maximizing profits and ROI, however. Data analytics can provide critical information for healthcare (health informatics), crime prevention, and environmental protection. These applications of data analytics use these techniques to improve our world.
Though statistics and data analysis have always been used in scientific research, advanced analytic techniques and big data allow for many new insights. These techniques can find trends in complex systems. Researchers are currently using machine learning to protect wildlife.
The use of data analytics in healthcare is already widespread. Predicting patient outcomes, efficiently allocating funding and improving diagnostic techniques are just a few examples of how data analytics is revolutionizing healthcare. The pharmaceutical industry is also being revolutionized by machine learning. Drug discovery is a complex task with many variables. Machine learning can greatly improve drug discovery. Pharmaceutical companies also use data analytics to understand the market for drugs and predict their sales.
#EMBA27 Applications of Probability Theory