The past couple of decades have witnessed exponential growth in data, due to the penetration of information technology across all aspects of science and society; the increasing ease with which we are able to collect more data; and the growth of Internet-scale, planet-wide Web-based and mobile services-leading to the notion of "big data". While the emphasis so far has been on developing technologies to manage the volume, velocity, and variety of the data, and to exploit available data assets via machine learning techniques, going forward the emphasis must also be on translational data science and the responsible use of all of these data in real-world applications. Data science in the 21st century must provide trust in the data and provide responsible and trustworthy techniques and systems by supporting the notions of transparency, interpretability, and reproducibility. The future offers exciting opportunities for transdisciplinary research and convergence among disciplines-computer science, statistics, mathematics, and the full range of disciplines that impact all aspects of society. Econometrics and economics can find an important role in this convergence of ideas.