Research Of Visualization Platform For Multi-dimensional Data

Improvement of information technology brought us convenience in recent years, while accelerate data explosion in this society. Storage and processing of massive data is more and more important in computer science. Especially accessing usefull information from massive data and displaying data in much more intuitive way to manager are urgent issues in front of researchers.This work is mainly on how to organize massive data and data display of OLAP data using theory of dataware house and OLAP cube. We propose a navigating solution which can help us to explore cube data efficiently and clearly. In the process of exploration, we use conditions to drilling cube data step by step, and dimensions of a cube are reduced simultaneously. Based on this, our study is mainly on data extracting and data display. Besides, we discuss about more flexiable and intuitive interaction to make users anysis data convenient.We present a solution of reducing dimensions using conditional filtering.Users can explore OLAP data step by step to narrow their intresting scope and build their intresting hierarchy. Based on exoploration result, we anylsis users’intresting hierarchy and the relationship of exploration results to optimize data exploration; this can reduce the complexity of exploration. Based on data exploration, we researched on OLAP and data display, we propursed a data extracting anylize method according OLAP cube and on line anylsis. We define anylsis model, search model, display model according all aspects of data display. Besides, we present a more flexable solution to display data based on data exploration and data display which reduced complex of multidimension data display.The solution can be used in nearly all multi-dimensional data in many fields, and we implemented it use a light and rich internet application.this solution reduce the complexity of data display in multi-dimensional data.