Goods value data analysis method and system

Abstract

The invention discloses a goods value data analysis method and system. The method comprises the following steps: collecting and storing real estate goods value data, collecting goods value data of each service in each stage in real estate operation through a preset component, configuring conversion, scheduling, monitoring and transmission of the goods value data, and storing the goods value data into a set template; and calculating real estate goods value data, and performing real estate full-cycle analysis and calculation on the goods value data by adopting a big data technology. The invention at least has the following beneficial effects: the full-cycle goods value data acquisition and analysis method for the real estate industry is provided, data from different sources in the industry can be acquired, so that the data from different sources, in different formats and with different properties are organically centralized logically or physically; through effective data circulation andefficient management between applications, data aggregation is achieved, and then rapid analysis and calculation of real estate full-cycle goods value data are achieved.

Description

technical field [0001] The invention relates to the technical field of computer data analysis, in particular to a value data analysis method and system. Background technique [0002] As the real estate industry enters into refined operations, the early real estate value analysis is no longer applicable to the current refined operation needs. The early real estate value analysis is in charge of the marketing, and the marketing will only be correct after obtaining the pre-sale certificate. At this time, it is already at the end of the value chain of the real estate cycle, and the value of real estate can be basically determined in the design and planning stage. In addition, the current real estate industry systems are scattered and independent. Data resources between businesses are not only isolated, but the consistency and interoperability of data resources are also poor. The value of data resources cannot be fully utilized. Integration is also without rules. Traditional da...

AI Technical Summary

Problems solved by technology

In addition, the current real estate industry systems are scattered and independent. Data resources between businesses are not only isolated, but the consistency and interoperability of data resources are also poor. The value of data resources cannot be fully utilized. Integration also has no rules to follow

Traditional data warehouses only take the structured data of one or two systems due to storage and calculation problems. The data scale of the systems involved in the full cycle of real estate value data will reach TB level and there are various database types and multiple data structures. When the data scale of traditional digital data reaches the terabyte level, the analysis and mining capabilities become weaker

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