Well, let’s start by exploring what data-science means. I found this definition of data-science:
At a high level, data science is a set of fundamental principles that guide the extraction of knowledge from data
Foster Provost and Tom Fawcett in Data Science for Business
They put it into perspective by writing:
Data science involves principles, processes, and techniques for understanding phenomena via the (automated) analysis of data. The ultimate goal of data science is improving decision making, as this is generally of direct interest in business.
Foster Provost and Tom Fawcett in Data Science for Business
In general it’s about extracting knowledge out of data for the purpose of decision making. This also may involve automatic processes which can lead to automated decision making.
Wikipedia goes in the same direction:
Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.
Wikipedia
Conclusion
Data science is used to extract knowledge from data whether it’s for gaining insides from data or help with making decisions (often business decisions).
In the next posts I will dig deeper into the techniques and processes that are needed extract this knowledge (for example data-mining). The definition of data-science is the start for our journey through this field. We’ll cover the fundamental basics and further down the road learn the technical skills to actually practice this principles and methods.