In recent years there has been an increasing interest in understanding how organizations can utilize big data in their process management to create value and improve their processes. This is due to new challenges for process management which have arisen from increasing competition and the complexity of large data sets due to technological advancements. These large data sets have been described by scholars as big data which involves data that are so complex traditional data analysis software are not sufficient in managing or analyzing them. Because of the complexity of handling such great volumes of data there is a big gap in practical examples where organizations have incorporated big data in their process management. Therefore, in order to fill relevant gaps and contribute to advancements in this field, this thesis will explore how big data can contribute to improved process management. Hence, the aim of this thesis entailed investigating how, why and to what extent big data is used in process management. As well as to outline the purpose and challenges of using big data in process management. This was accomplished through a literature review and a survey, respectively, in order to understand how big data had previously been used to create value and improve processes in organizations. From the extensive literature review, an analysis matrix of how big data is used in process management is provided through the intersections between big data and process management dimensions. The analysis matrix showed that most of the instances in which big data was used in process management were in process analysis & improvement and process control & agility. Simply put, organizations used big data in specific activities involved in process management but not in a holistic manner. Furthermore, the limited findings from the survey indicate that the main challenges and purposes of big data use in Swedish organizations are the complexity of handling data and making statistically better decisions, respectively.