Big data is gaining increasing attention from the ports and shipping industry . The analysis and exploitation of shipping data can provide government departments and functional state-owned enterprises with elementary data so that they may play a better role in public service . However,the exploitation of shipping data faces several difficult problems . Firstly,the government and state-owned enterprises do not have enough qualified human resources to process big data,so they have to rely on universities and research institutes .Secondly,since shipping data are of great commercial value,data security and business privacy are of extreme importance during its storage and transmission .Thirdly,the data assets of the shipping enterprises need to be evaluated,and an equitable mechanism of profit distribution should be set up on the basis of the ownership of data . Finally,the efficient employment of shipping big data involves the integration of various sources in order to realize the sharing of data and resources,which requires the establishment of relevant policies by the government to promote data sharing in public service . Managing big data will bring greater profit to various sections of public service and lead to broader application prospects once the above problems are solved .Firstly,realtime data mining on the shipping data will make the shipping index more accurate as it reflects the changes of the industry more quickly than traditional shipping indices .Secondly,the containers at different container yards can be dynamically allocated and distributed when the data are monitored and processed in realtime,so that the operation efficiency of shipping enterprises is raised and social cost is saved .Thirdly,the shipping data can be used to inspect enterprises' credit rating and provide information on the actual operation of enterprises at fast speed and low cost,assisting the development of the supply chain finance .Fourthly,realtime monitoring of customs application data will facilitate the discovery of questionable products and missing information and give pre-warning to export-oriented enterprises,greatly reducing their risks and losses . In the future,shipping big data should be firstly integrated with the cloud infrastructure by benefiting from standard software and hardware and elastic computing resource allocation . Secondly,the data governance architecture inside the organization needs to be improved . Shipping data from variance sources should be cleaned and mended before further analysis and processing .Thirdly,data inside the organization should be grouped and partitioned in order to fulfill different requirements .Finally,a shipping big data ecosystem is proposed to realize the sharing of data among all interested individuals and companies . With big data technology developing at fast speed,the supervision departments and relevant service enterprises should adopt reliable and well-established solutions to construct an analytical platform for big data .