Multi-dimensional data acquisition device, system and method

Abstract

The invention provides a multi-dimensional data acquisition device, system and method. The multi-dimensional data acquisition device comprises: an acquisition component which acquires multi-dimensional target data acquired by a plurality of data sources, determines a configuration interface for processing the multi-dimensional target data and a matching rule corresponding to the configuration interface according to the attribute information of the multi-dimensional target data, generates a data division strategy according to the interface information of the configuration interface and a matching rule corresponding to the configuration interface, and divides the multi-dimensional target data according to a data division strategy to obtain a plurality of data sets; and a data interaction center which sends the plurality of data sets to a storage component for storage. The division strategy is generated through the configuration interface of the target data and the matching rule corresponding to the configuration interface, and the divided data set is processed and then sent to the storage structure and a sharing platform, so that conversion of the target data is more flexible, and the practicability of conversion and sharing of the target data is enhanced.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to a multi-dimensional data acquisition device, system and method. Background technique [0002] With the development of software and hardware, the era of big data has opened an era of large-scale production, sharing and application of data, and the interaction of information has become more and more commonplace. In various business application scenarios, data collection and application are widely used, and this phenomenon has formed a new business form. Compared with traditional data collection, the era of big data has a wide range of data sources, a large amount of data, and rich data types. [0003] However, due to the differentiation of data types, it is usually necessary to rely on various types of sensors for collection, which inevitably leads to the phenomenon of connecting multiple sensors on the local system, which is messy and inconvenient for management...

AI Technical Summary

Problems solved by technology

[0003] However, due to the differentiation of data types, it is usually necessary to rely on various types of sensors for collection, which inevitably leads to the phenomenon of connecting multiple sensors on the local system, which is messy and inconvenient for management and maintenance. In addition, due to the need for various Different types of sensors are used for data collection, which makes the data sources scattered and diverse, making it difficult to integrate and fuse data

[0004] In the prior art, many data collection ETL tools can also support data collection in multiple formats, but the existing ETL tools are all based on database service collection, and such tools need to spend a lot of time in data cleaning, and in the data In the conversion process, the data conversion cache table is needed to realize it. Since the completion of a job corresponds to a data attribute conversion, hundreds or dozens of jobs need to be managed at every turn, and client management is difficult to arrange, resulting in insufficient flexibility of data conversion.

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