Abstract
With the increasing amount of information, the percentage of processed large-scale heterogeneous data is rapidly growing. Take mobile phones as an example. Due to their various sensors, high presence among people, and cost-effectiveness, they are becoming very popular. This has made it easy to obtain users' contextual data whose collection can be valuable in engineering and business domains, e.g., transportation, location-based services, and advertisement industry. The data volume generated by mobile phones and the need to analyze the information near the real-time are the challenges facing researchers. Recently, big data has attracted much attention from academia, industry as well as government. There is a strong need for new technologies, e.g., frameworks based on cloud computing, that could not only process and analyze a large volume of data, but also ingest a large volume of data at a fast pace. In this paper, we propose to use a dynamic data analysis framework to explore and analyze mobile phone data. After preprocessing the dataset consisting of cell phone communication records, this paper presents an interactive exploratory spatial data analysis algorithm and its analysis results.