Multi-dimensional database system based on financial data analysis and implementation method

Abstract

The invention discloses a multi-dimensional database system based on financial data analysis. The system comprises a data acquisition terminal, a data ETL processing server, a data warehouse server and a multi-dimensional data analysis server; the data acquisition terminal is connected with the data ETL processing server, and the data ETL processing server is connected with the data warehouse server; the data warehouse server is connected with the multi-dimensional data analysis server. The data ETL processing server converts original financial data into a specific format, then integration isconducted in the data warehouse server, the integrated data in a data warehouse is used for constructing a multi-dimensional data model in the multi-dimensional data analysis server and forming a plurality of data marts, and then comprehensive analysis is carried out, so that data query and access are facilitated, and then the access rate is increased.

Description

technical field [0001] The invention belongs to the field of financial analysis, and relates to a multidimensional database system based on financial data analysis and a realization method. Background technique [0002] Under the environment of rapid economic development in our country, group enterprises are also rapidly expanding and developing at a high speed. After long-term operation, the business and financial systems of the group companies have accumulated a large amount of data, but these large amounts of data are only existing and relevant. In each financial information system, the data has not been fully utilized, and the value of the data has not been reflected. The status quo of enterprise data application is mainly reflected in the following aspects: (1) enterprises have accumulated a large amount of data; (2) data is scattered and stored, and it is difficult to implement comprehensive analysis and application; (3) there are many types of reports, it is difficult...

AI Technical Summary

Problems solved by technology

The status quo of enterprise data application is mainly reflected in the following aspects: (1) enterprises have accumulated a large amount of data; (2) data is scattered and stored, and it is difficult to implement comprehensive analysis and application; (3) there are many types of reports, it is difficult to summarize, and data is prone to errors; 4) It is difficult to do predictive analysis; (5) It is impossible to carry out collaborative decision-making around the group's strategic goals

[0003] The financial system only solves the process and standardization of the financial general ledger. The database is designed according to the traditional ER design model and follows the paradigm rules in database design. Therefore, data storage is convenient and the consistency and integrity of the data are preserved, but it is not conducive to multi-dimensional query and analysis, less efficient

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