What’s the difference?
There is confusion over the terms Data Science and Big Data. So what these terms mean on real-world projects?
Data Science looks to create models that capture the underlying patterns of complex systems, and codify those models into working applications.
Data Science insights obtained are used for business decision making or for research purposes.
Big Data looks to collect and manage large amounts of varied data to serve large-scale web applications and vast sensor networks.
Big data is analyzed for insights that lead to better decisions and strategic business moves.
Although both offer the potential to produce value from data, the fundamental difference between Data Science and Big Data can be summarized in one statement:
Collecting Does Not Mean Discovering
Data science is the umbrella term. Big data comes under data science.