The digital world has a wealth of data, such as internet of things (IoT) data, business data, health data, mobile data, urban data, security data, and many more, in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting knowledge or useful insights from these data can be used for in various applications domains. In the area of data science, methods including modeling can provide actionable insights or deeper knowledge about data, which makes the process automatic and smart. In this paper, we present a comprehensive view on "Data Science" including various types of advanced analytics methods that can be applied to enhance the intelligence and capabilities of an application through smart decision-making in different scenarios. We also discuss and summarize ten potential real-world including business, healthcare, cybersecurity, urban and rural data science, and so on by taking into account data-driven smart computing and decision making. Based on this, we finally highlight the challenges and potential within the scope of our study. Overall, this paper aims to serve as a reference point on and to the researchers and decision-makers as well as application developers, particularly from the data-driven solution point of view for real-world problems.