Research and application practice of “Multi- Data Lake under One Middle-Platform” industrial big data platform based on Lakehouse technology

With the explosive growth of data volume in the era of the digital economy, data platforms are facing increasing challenges in data storage, processing, and calculation. This paper proposes multiple Data Lakes under a unified Data Middle Platform, which is applied in industrial big data. The architecture, based on the integration of lake and warehouse technology, aims to build an efficient, flexible, and scalable data management platform to support cross-level, cross-organizational, and cross-regional data-sharing applications. With the centralized deployment of the three-level data lake and the middle platform deployed uniformly, the five core functions are constructed, forming the dataacquisition capabilities of multi-source heterogeneous data, multi-mode data storage, data processing, data governance, data service, and data security protection. Through multi-data-lakes, collaborative interaction, and unified data control ability, to realize the overall management and open sharing of data of super-large group companies, application scenarios in various business fields are supported, and the value of data elements is released.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-01-01
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
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article

Research and application practice of “Multi- Data Lake under One Middle-Platform” industrial big data platform based on Lakehouse technology

SHILAP Revista de lepidopterología
Diverse Scientific and Economic Studies
article

Research and application practice of “Multi- Data Lake under One Middle-Platform” industrial big data platform based on Lakehouse technology

article en

Abstract

With the explosive growth of data volume in the era of the digital economy, data platforms are facing increasing challenges in data storage, processing, and calculation. This paper proposes multiple Data Lakes under a unified Data Middle Platform, which is applied in industrial big data. The architecture, based on the integration of lake and warehouse technology, aims to build an efficient, flexible, and scalable data management platform to support cross-level, cross-organizational, and cross-regional data-sharing applications. With the centralized deployment of the three-level data lake and the middle platform deployed uniformly, the five core functions are constructed, forming the dataacquisition capabilities of multi-source heterogeneous data, multi-mode data storage, data processing, data governance, data service, and data security protection. Through multi-data-lakes, collaborative interaction, and unified data control ability, to realize the overall management and open sharing of data of super-large group companies, application scenarios in various business fields are supported, and the value of data elements is released.

SHILAP Revista de lepidopterología
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Diverse Scientific and Economic Studies
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