This Thor-Olavsrud article provides a useful introduction to some of the concepts, tools, and uses of data science.
These include:

  1. What is data science
  2. Data science vs. analytics
  3. Data science vs. big data
  4. The business value of data science
  5. Embedded approach
  6. Data science tools
  7. Data science salaries
  8. Data science skills

“Data science is a method for transforming business data into assets that help organizations improve revenue, reduce costs, seize business opportunities, improve customer experience, and more.

What is data science?

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. For most organizations, data science is employed to transform data into value that might come in the form improved revenue, reduced costs, business agility, improved customer experience, the development of new products, and the like.

“The amount of data you can grab, if you want, is immense, but if you’re not doing anything with it, turning it into something interesting, what good is it? Data science is about giving that data a purpose,” says Adam Hunt, chief data scientist at RiskIQ.

Data science vs. analytics

While closely related, data analytics is often viewed as a component of data science, used to understand what an organization’s data looks like. Data science takes the output of analytics to solve problems. ”

Continue reading Thor Olavsrud’s article.