Abstract: Aiming at the problem that the scattered data was easy to lose frame when the data was randomly forwarded in the integrated data interaction center, the author proposed a lossless restoration method based on big data analysis. Firstly, big data bit sequence was formed by collecting scattered defect information in the data interaction center of cloud storage, and the storage structure model of data in cloud computing center was analyzed. Secondly, the feature decomposition of scattered defect information was carried out by using the method of joint sparse decompo
sition,  the feature compression and adaptive feature clustering processing of information of scattered defect information were carried out by using compression perception method, combined with big data information fusion method, and the association feature mining of scattered defect information was carried out. Finally, the method of phase space reconstruction was used to reconstruct the features of scattered defect information, and the lossless information of scattered defect information was restored in the reconstructed phase space. The simulation results
 show that the error of lossless restoration of scattered information is lower, the precision of data reconstruction is higher, the computation cost is small, and the ability of information restoration is improved effectively.

Key words: big data analysis, scattered defect, lossless restoration, phase space reconstruction