Dhar presents a theory of data science that addresses challenges and caveats for dealing with big data. The study is well documented and easy to read for a wide audience. It is a useful guide to understand timely challenges in the area of big data. The review fits well with recent developments in knowledge modeling and the semantic web. The article presents a new perspective on big data and demonstrates this with real-world situations.

Dhar argues that we are moving toward a big data era in which computers will be better decision makers than people in many situations. Though that is a bold statement, it is true to a great extent. Dhar emphasizes the limitations of knowledge discovery techniques by claiming that all models are wrong, yet some are useful. The article explains the usefulness of machine learning as an approach for discovering interesting data patterns. Dhar argues that big data helps in reducing errors resulting from misspecifications of a model and small samples by enabling validation. He concludes that big data makes it feasible to uncover the causal models generating the data by using machine learning to model big data.