The Facebook-Cambridge Analytica data scandal shows evidence that there is no such thing as a free lunch in the digital world. Online platform companies exchange “free” goods and services for consumer data, reaping potentially significant economic benefits by monetizing those data. Phrases such as “free goods” are misnomers. Welfare analysis on digital goods or services without considering the value of data can mislead policy analysis. In this research, we classify online platforms into eight major types based on underlying business models, and conduct case studies to analyze data activities related to each type. We show how online platform companies take steps to create the value of data, and present the data value chain to show how the value of data varies by step. We find that online platform companies can vary in the degree of vertical integration in the data value chain, and the variation can determine how they monetize their data and how much economic benefits they can capture. Unlike R&D that may depreciate due to obsolescence, data can produce new values through data fusion, a unique feature that can create unprecedented challenges in measurements. Our initial estimation shows that the value of data can be tremendous. Moreover, online platform companies can capture most benefits of the data, because they create the value of data and consumers lack knowledge to value their own data. Lastly, the Internet of Things, the trend of 5G, and the emerging online-to-offline transition are accelerating the speed of data accumulation. The valuation of data will have important policy implications for investment, trade, and growth.