When people are talking about data science in today’s business, they are thinking of Big data, Hadoop ecosystem, Open data, Skill set such as R, Python, Spark, and machine learning. I believe they got it wrong! Data science is focusing on data, and is about how to extract the information/pattern from data. All the others are just tools, like language, that help you to achieve the goal.
So what’s the difference between the old name such as data analyst, data miner and the fancy name data scientist? I once got it wrong by thinking data scientist is about mining big dataset via fancy machine learning black box and using R, Spark, Python. For sure these skills from programming to machine learning are the key to be a successful data scientist, but the core of data science is about innovation (the term in business world) or research (the term in academic world).
Data science in business and in academic are all doing the same thing, i.e. trying to use the new methodology, approach to tackle the old problems. Hence all data scientists need to have critical thinking, and bury classical approach.