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Based on the traditional data management system and big data management system was introduced, the comparative analysis of the traditional data management system and big data management system from the aspects of thinking method, data storage technology and data processing technology. Make people realize that with the development of the information age, the advantage of big data management system is better than the traditional data management system. With the development of information-based society, networking and intelligent and the popularity of Internet, networking and intelligent terminal, people's lives gradually entered by the knowledge explosion times to the explosion of data, data has become today's new production factors and strategic resources, much of the industry and relevant government departments to focus on . Data management system is the most direct data processing tools, but with the increase in the amount of data, the type of complex, the data management put forward higher requirements. Many of the industry in the face of massive, multi-source heterogeneous data, the traditional data processing system is facing storage and analysis processing bottleneck, and data management system appeared to solve the many technical problems in the traditional data management system. The traditional data management system and data system is to deal with the analysis of data in valuable information and knowledge for the purpose, but technology development background, environmental data, analysis processing depth, breadth and the thinking mode of, the traditional data management system and data system there is a big difference. 1 . Traditional data management systems and large data management system The traditional data management system and data management system there is a big difference, first of all on the definition are compared, the data management system can be seen as the upgrading of the traditional data management system, a higher data processing. 1.1 traditional data management system The traditional data management system is refers to from a large number of real data through a specific algorithm analysis of each data, within the acceptable computational resources to find the law, the automatic extraction of implicit, past the unknown, valuable potential information and analysis is the real data may is incomplete, noisy, fuzzy and random [3]. 1.2 data management system Data management system can be understood as many complex data together analysis and processing, inside the potential value, knowledge is extracted, make people realize that things in the global, and can predict the future trends of the system. Big data system for today's data stream processing has its unique advantages, unapt make people lost in the information society of the massive complex data in the tide. The traditional information management system with large data platform from three aspects: (1)the traditional information management system is generally used for a realistic generated data, big data management is based on the analysis of existing data. 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer (MMEBC 2016) © 2016. The authors Published by Atlantis Press 919 (2)the traditional data management system is a linear analysis, big data analysis processing system using parallel logic. (3)the traditional information management system is focus on simple data applications, large data management system for global analysis and application of [4]. 2 traditional data management systems and big data management system of thinking difference The big data era, opened a new era of transformation, and has brought about great changes in people's work and life thinking. The era of big data thinking embodied in three aspects. (1) the transition from causal relationship to. Change the idea to solve the problem, big data concerned about the relationship between data, rather than tangled in difficult to figure out the cause and effect relationship. (2) from the exact transition to hybrid. In the face of the rapid growth of multi-source heterogeneous data, the analysis of the data is constantly expanding, ignoring the micro level of precision, chasing the macro level of the law of the development of things and direction. (3) analysis of transition from random samples to all data. When analyzing the data, not close to a small part of the data, to make use of all the data, and to make full use of [5]. The traditional data management thinking that data to be stationary, once after processing and analysis, the data would become old and useless data, and data systems that data is in motion, not static nor divided into the old and the new and pay more attention to the cross correlation comparison of old and new data. Proposed solution programme Problems arise logic analysis Find the cause and effect relationship Make the optimization scheme Find relevance Traditional management process Quantitative analysis Data collection Big data management process Figure 1 traditional data management and big data management thinking difference The traditional method of small data is found, by logical analysis, the causal relationship is proposed to solve the problem. The method of big data is through large-scale data collection, through quantitative analysis, put forward the associated relationship, make the optimization scheme. Big data management and the traditional management mode of thinking difference as shown in figure 1. Different thinking patterns are mainly embodied in the causation of liberation from the people to a great extent, and more focus on the use of the associated relationship and discovery. Big data thinking is mainly to tell us what is rather than why, do not have to know the reasons behind the phenomenon. Sampling has been hailed as one of the greatest achievements of the twentieth Century[6], its advantages are through the sample, the survey, access to data, and then on the overall inference. Sampling deliberately avoided the detail investigation. However, in many areas, part of the data collection has as much as possible to the data collection transformation, sampling has been unable to achieve the depth of data and analysis of wide crossing with the use of. Random sampling is a temporary data, as you collect more and more data, the prediction results will be more accurate. Thus our data processing has occurred earth shaking change, and our thinking has not changed. Therefore, we should abandon sample analysis this shortcut, complete and comprehensive data collection.

Comparative analysis of data management system