The English used in this article or section may not be easy for everybody to understand. (April 2014)
Data science is the study of the extraction of knowledge from data. It uses various techniques from many fields, including signal processing, mathematics, probability models, machine learning, computer programming, statistics, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high performance computing with the goal of extracting useful knowledge from the data. Data Science is not restricted to only big data, although the fact that data is scaling up makes big data an important aspect of data science.
A person that takes the role of data science is called a data scientist. Data scientists solve complicated data problems using many elements of mathematics, statistics and computer science, although skill in these subjects are not required. However, a data scientist is most likely to be an expert in only one or two of these disciplines, meaning that cross disciplinary teams can be a key component of data science.
Good data scientists are able to apply their skills to achieve a broad spectrum of end results. The skill-sets and competencies that data scientists employ vary widely.