AIMDP: An Artificial Intelligence Modern Data Platform. Use case for Spanish national health service data silo

计算机科学 工作流程 数据仓库 大数据 数据治理 数据管理 数据科学 服务(商务) 数据挖掘 数据库 数据质量 经济 经济
作者
Alberto S. Ortega-Calvo,Roberto Morcillo-Jiménez,Carlos Fernandez‐Basso,Karel Gutiérrez‐Batista,M. A. Vila,María J. Martín-Bautista
出处
期刊:Future Generation Computer Systems [Elsevier]
卷期号:143: 248-264 被引量:11
标识
DOI:10.1016/j.future.2023.02.002
摘要

The huge amount of data being handled today in any environment, such as energy, economics or healthcare, makes data management systems key to extracting information, analysing and creating more efficient daily processes in these environments. However, the inability of current systems to take advantage of the data generated can waste good opportunities for analysing and extracting information from the data. Modern data platforms (MDP) appear suitable for supporting management systems and are able to perform future prospective analyses. This paper presents a data platform called Artificial Intelligence Modern Data Platform (AIMDP), based on Big Data, artificial intelligence for management, and efficient data handling. The different components of AIMDP intervene in the data acquisition phase and implement algorithms capable of analysing massive data collected from heterogeneous sources. In addition, the entire platform is geared towards data management and exploitation with a layer of security and data governance that allows the integrity and privacy of the databases to be maintained. The proposed platform is designed to be used by users who are not experts in data science. To this end, it implements a user-oriented workflow that has effectively been introduced in a use case of two Spanish hospitals to extract knowledge from their historical data, which had been siloed and had never been explored by any hospital researchers or doctors.
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