Data science is a broad area of study that incorporates elements of various academic disciplines, including computer science, mathematics and statistical analysis. Essentially, the purpose of the field is to develop methods to quantify and interpret massive amounts of information. While data science is relatively new compared to many other academic pursuits, it has already garnered significant attention across virtually all industries. The discipline has numerous commercial applications, especially for large companies that serve thousands or millions of customers.
As an interdisciplinary field, the study of data science requires intimate knowledge of multiple component disciplines. Computer science has become a staple for students and practitioners of the profession, but familiarity with math and statistics are also critical. Since many data scientists apply their skills for commercial clients or employers, they also need a firm understanding of business and general communications ability. Data science represents a joint discipline that combines aspects of science, business and communications to provide comprehensive analytical capability.
Principles of Data Science
Data scientists apply both theoretical and practical expertise in their work, and often use the scientific method to refine their process to improve the accuracy of results over time. Depending on their specific area of work, scientists may primarily use structured or unstructured data. Structured data is the result of scientific measurement like electronic sensors, networking traffic and global position system (GPS) information. Using unstructured data, like customer reviews, is more complicated because it requires curation and quantification before it can be consistently analyzed.
The ability to make sense of large amounts of information is useful in almost any area of commerce, government or science. However, there are currently a handful of areas where it has proven to be particularly valuable. As one of the biggest collectors and users of data on the internet, many e-commerce destinations are actively expanding their use of data scientists in their analytic efforts. Data science is also applied to social networking, healthcare, telecommunications and government projects, according to the US Bureau of Labor Statistics (BLS).
Working as a Data Scientist
Scientists who work with “big data” may find themselves participating in a wide variety of professional activities as part of their job. Some data scientists have to “scrub” their data before using it, which requires them to organize it and check for potential errors that could impact their findings. Even with data from a reliable and credible source, data science professionals still have to develop a strategy for measuring the information and create models with advanced software. In many business settings, they are also expected to present their findings through visual renderings and presentations to company decision makers.
As a relatively new field of study, there are still a lot of unknowns about the future of data science in the modern marketplace. Despite these uncertainties, current trends indicate a growing demand for qualified professionals who can apply the principles and skills of the profession for clients. Understanding how data science works is certainly crucial for the scientists themselves, but can also be useful for anyone practicing business or financial analysis.