In the past decade, we have witnessed the rapid development of data science and its wide applications in the information technology (IT) industry. Data science has also offered new solutions and created new opportunities for many other areas, including sustainability. Many fields related to sustainability rely on the collection, compilation, analysis, and presentation of various types of data with distinct characteristics. In this talk, I will discuss my understanding of data science, its (potential) applications in some relevant fields in sustainability, and some case studies. These case studies include using link prediction and machine learning methods to estimate missing data for life cycle assessment (LCA), identifying principle indicators for Sustainable Development Goals (SDGs), and estimating spatiotemporal distribution of urban air quality based on low-cost sensors.