AI data warehouse platform and operation method

A technology of data warehouse and platform, which is applied in the field of AI data warehouse operation and AI data warehouse platform to achieve the effect of convenient management
CN110297869AActive Publication Date: 2019-10-01BEIJING BAIDU NETCOM SCI & TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING BAIDU NETCOM SCI & TECH CO LTD
Publication Date
2019-10-01

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Abstract

The invention relates to the field of data storage, and specifically relates to an AI data warehouse platform. The platform comprises a business layer module which is used for receiving a business request of an AI product, sending a corresponding operation request to a service layer module and forwarding feedback of the service layer module to the AI product so as to realize a function corresponding to the business request; a service layer module used for receiving the operation request of the business layer module and carrying out corresponding operation on the storage layer module; an operation result of the storage layer module being fed back to the corresponding sub-module in the service layer module; and a storage layer module used for processing and storing the AI data according to the operation of the service layer module. The invention further provides an operation method of the AI data warehouse. The AI data storage method and device are suitable for AI data storage above thePB magnitude, the storage efficiency can be improved, the storage cost can be reduced, and the value of the AI data can be brought into full play.
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Description

technical field

[0001] The present invention relates to the field of data storage, in particular to an AI data warehouse platform and an AI data warehouse operation method. Background technique

[0002] With the application of artificial intelligence (AI) technology in more and more business scenarios, a large amount of AI data is generated every day, including various types of multimedia data such as video, image, audio, and text. The storage, processing, query, and update of large-scale AI data have brought great challenges to traditional data warehouses. It is precisely this large amount of AI data that promotes the continuous iteration, optimization, and upgrading of related AI models to better Service-related business scenario requirements. Different from the large-scale user behavior data generated in the traditional Internet era, AI data is often various types of multimedia data, so there is a big difference from traditional big data in the way of data collection, st...

Claims

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