Big data asset quality assessment method

Abstract

In the invention, data scenes are divided according to industry business characteristics, data scene information factor is determined, a data configuration baseline for judging the validity of the data sample is defined; the effective data scale and the effective data proportionality coefficient of each data scene are calculated, a data effective index is calculated by utilizing scene informationfactor weighting, a data diversity index is calculated according to the effective data proportionality coefficient, and finally comprehensive calculation on the data effective index and the diversityindex is performed to obtain a data quality index. According to the technical scheme of the invention, the data quality index is comprehensively evaluated from two main dimensions of data validity and data diversity; the relatively complete data quality assessment method is provided, a relatively universal method framework and a flexible processing strategy are adopted from macroscopic view to microscopic view, the application expansibility is good, and the scheme requirements of data quality assessment of different industries can be met. The scheme has the advantages of high operability andhigh engineering practice value.

Description

technical field [0001] The invention relates to the technical field of asset evaluation, in particular to a method for evaluating the quality of big data assets. Background technique [0002] In the long-term operation of enterprises in various industries, a large amount of data has been accumulated, such as environmental data, equipment data, monitoring data, sensor data, financial statement data, consumption data, etc. These data can not only provide decision-making basis for company operations, but also It can be used as an important part of intangible assets for enterprise valuation. In the era of big data and artificial intelligence, big data is more important than artificial intelligence algorithms in a certain sense. Therefore, data assets and data quality have an important impact on the current and future value of enterprises. [0003] Based on the above considerations, in recent years, the industry has launched related research on data assets and quality assessment...

AI Technical Summary

Problems solved by technology

Another example is CN106845846A (big data asset evaluation method). This scheme does not reflect the evaluation processing method in terms of data scene diversity, and data diversity is also an important part of data quality. At the same time, the performance parameters of data samples also have a direct impact on data quality. effect, which is not reflected in the method

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