Data Science has brought a revolution in the way data is being handled, collected, recorded, analysed and presented. This has led to many contrasting views and change of policies by many Companies. This is what you need to know about majority of the policies and about the so-called 'partners'. So, what really is data? And what about the fuzz around data science?
1. Introduction
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data: "use the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems".
Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, and information science.
Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it... — Dan Ariely
This quote is so apt. Many junior data scientists I know (this includes myself) wanted to get into data science because it was all about solving complex problems with cool new machine learning algorithms that make huge impact on a business. However, you may still need to readjust your expectations of what to expect from a data science role.