Rapid Construction of a Big Data Analysis System with Creative Comparison Methods

Data query comparison of large data should process a large number of datasets, which is the core for basic research projects. In the selection of analysis factors, how to choose a better way to provide data analysis library can be very helpful for quickly analysis and search comparison. In this study, we try to design and study, improve the speed of data query and comparison in big datasets, and find a similar bleak analysis, construct data fuzzy comparison after the results of modelling analysis. How to filter out relevant quarries and utilise creative elements may be able to mate the results. In the case studies, the proposed method will be carried out through artificial experience analysis and extraction for analysis results, and it will also be further applied to different industry analysis techniques.In this study, we used creative data engineering to reorganise unknown information from the database first. After the data collection, we aim to find possible similar variable factors and combine them with the data structure management. Thirdly, through the intersection of information quickly query, relevant data can be drawn to cross-matching pre-established models. When relevant factors change, we allow different aggregation. Finally, after the selection, our study can analyse and select all the data structure of the original non-relevance of the field data to find out the relevance of the results.