What Is Data Science?

A few years ago, few people outside of the Bay Area could answer that question. Now, after Harvard Business Review labeled data scientists the sexiest job of the 21st century and Glassdoor named it as the best job for work-life balance, every organization is searching for one. How did this demand for data scientists exponentially grow overnight?

Our hyper-connected world is producing exponentially growing amounts of data that organizations, companies, and even governments are struggling to compile, process, and analyze. Billions of transactions and transmittals take place every day, creating a variety of opportunities and jobs in areas such as big data for companies in and out of the tech scene. Furthermore, the price of the hardware and software necessary to store, mine, and analyze this data is now more affordable than ever, allowing almost any organization to leverage its own data. This also makes it possible for companies to do sophisticated analyses on datasets that may or may not be considered “big data.”

These massive data clouds have proved to produce valuable insights for businesses, governments, and research labs. Where society created a problem, the business world saw an opportunity, and this opened the door for the field of data science.

Big Data

In modern times, so much data has been collected that it is hard to make any sense of it without the right analysis. One of the most important areas of data science is big data. Big data refers to the enormous quantity of data that is often available to data scientists. There is no set criteria for how big big data has to be in order to be considered “big data”, but it is too large for traditional analytical tools to be applied to it. With the use of the internet and various other technological advances, huge amounts of data are being produced each second by individuals. Think of all the Facebook posts, image uploads, document creations, and financial transactions you make each day. This data is collected by virtually all companies who then need data scientists to analyze the data and extract value from the mass of data. The remarkable quantity of data that is being produced every second is a huge contributor to why the demand for data scientists is so significant.

What Is Big Data Used For?

The existence of big data allows companies, research organization and businesses to analyze and make decisions based on a more complete source of information. It is responsible for a wide variety of advancements, making projects such as self-driving cars, and voice recognition in smartphones possible. Data scientists can pursue a career in fields besides technology or computer science, opening new opportunities to advance human welfare in areas such as psychology, economics, healthcare and medicine. Jobs in big data will produce large-scale impacts that will be felt worldwide.

What Does a Data Scientist Do?

Data scientists utilize skills from research design, computer programming, data analysis, statistics and mathematics to make sense of the data they analyze. Their goal is to channel the endless data being produced into something useful and valuable. Data scientists create customized, automated programs or applications to capture, organize, and analyze massive amounts of data, and they use that data to extract actionable information to help improve decision-making in an organization. Not only do data scientists find value in the data sets they are given, they also visualize and communicate their findings so that stakeholders can understand what they have found and use it to improve business.

A data scientist analyzes a complex problem from the inside out, taking a multifaceted approach to gain actionable insights from data. Their methods may include:

  • Statistical analysis
  • Time-series or graph analysis
  • Hadoop data management software
  • Statistical model building or predictive modeling
  • Analytics tools
  • Software engineering

Technologies such as cloud computing and distributed storage have reached a point where anyone with the appropriate skills can perform data science projects, though many companies are looking for data scientists with a graduate education. Technology has also been responsible for the explosion of data both in volume and in sources, as data from sources like real-time sensors, GPS coordinates from mobile phones, or personal wearable health devices are all contributing to this exponentially growing data universe. Data scientists will need to possess the skills to bring these two trends in line and moving them forward. For data scientists, the future is now.


Data Science Education

The first requirement in becoming a data scientist is to obtain some skills through university programs, such as analytical thinking, coding background, and familiarity with unstructured data. Luckily, a number of data science programs exist or are being developed to meet this significant level of demand for data science professionals. Several top-rated U.S. universities now offer dynamic master’s level programs that give students the essential data science skills for success.

Data Science Careers

After earning a degree in data science or a related field, the next step is to find a job as a data scientist. As the field of data science continues to take shape, jobs are emerging in corporations, universities, research facilities, and government entities. Every industry out there is employing data scientists to extract value from their data to improve their business. Discover which employers are seeking professionals with this advanced skill set, the average salary for data scientists, and how to find job opportunities.

Data Science in Business

Data scientists can extrapolate remarkable trends and analytics from streams of data. This has benefited corporations looking for a competitive advantage and researchers and scientists looking to break new ground, especially in the field of big data. Discover which companies are engaged in data science and which ones may soon be joining the fold. Learn more.