With the concept of a digital world taking precedence, our lives are being incessantly mapped and recorded in the digital realm. This, among other things, has led to availability of plethora of data that needs to be analysed in order to discover hidden patterns that are far from random. This is done through the field of Data Science. There are several definitions of data science available. Data science is considered to be an amalgamation of statistics, computer science, and application in various sectors. Large datasets of spatial and temporal information are assembled and manipulated in order to improve the understanding and management of complex systems. At its core, data science involves assemblage, management, and analysis of large spatio-temporal datasets for their translation into information that can eventually be used by decision makers for policymaking. Although data science is used in different domains, such as marketing, management, natural resource management, climate change studies, finances, development economics, among many others, an understanding of connection between the field of data science and sustainability is still limited.

Both the field of sustainability and data science being fairly new fields, there are a limited amount of academic resources that have been written about synergy between the two topics. A few academicians and professionals, however, are already working in data science applications for sustainability. Keeping this in mind, there is a need to strengthen the knowledge base by conducting capacity-building training programmes. The application of data science on sustainability can be examined through the triple bottom line/pillars (environment, social, and economic) perspectives.