Who Can Make Use of Data Science?

By Lillian Pierson

The terms data science and data engineering are often misused and confused, but these two fields are, in fact, separate and distinct domains of expertise.

Data science is the practice of using computational methods to derive valuable and actionable insights from raw datasets. Data engineering, on the other hand, is an engineering domain that’s dedicated to overcoming data-processing bottlenecks and data-handling problems for applications that utilize large volumes, varieties, and velocities of data. In both data science and data engineering, it’s common to work with the following three data varieties:

  • Structured data: Data that’s stored, processed, and manipulated in a traditional relational database management system.

  • Unstructured data: Data that’s commonly generated from human activities and that doesn’t fit into a structured database format.

  • Semi-structured data: Data that doesn’t fit into a structured database system, but is nonetheless structured by tags that are useful for creating a form of order and hierarchy in the data.

A lot of people think only large organizations that have massive funding are implementing data science methodologies to optimize and improve their business, but that’s not the case. The proliferation of data has created a demand for insights, and this demand is embedded in many aspects of our modern culture.

Data and the need for data insights are ubiquitous. Because organizations of all sizes are beginning to recognize that they’re immersed in a sink-or-swim, data-driven, competitive environment, data know-how emerges as a core and requisite function in almost every line of business.

So, what does this mean for the everyday person? First off, it means that our culture has changed, and you have to keep up. It doesn’t, however, mean that you must go back to school and complete a degree in statistics, computer science, or data science. In this respect, the data revolution isn’t so different from any other change that’s hit industry in the past.

The fact is, in order to stay relevant, you only need to take the time and effort to acquire the skills that keep you current. When it comes to learning how to do data science, you can take some courses, educate yourself through online resources, read books like this one, and attend events where you can learn what you need to know to stay on top of the game.

Who can use data science? You can. Your organization can. Your employer can. Anyone who has a bit of understanding and training can begin using data insights to improve their lives, their careers, and the well-being of their businesses. Data science represents a change in the way you approach the world.

People used to act and hope for an outcome, but data insights provide the vision people need to drive change and to make good things happen. You can use data insights to bring about the following types of changes:

  • Optimize business systems and returns on investment (those crucial ROIs) for any measurable activity.

  • Improve the effectiveness of sales and marketing initiatives — whether that be part of an organizational marketing campaign or simply a personal effort to secure better employment opportunities for yourself.

  • Keep ahead of the pack on the very latest developments in every arena.

  • Keep communities safer.

  • Help make the world a better place for those less fortunate.