作为云服务的大数据管理和分析

Research Paper, S. Alghamdi, Sarah Alghamdi, Yasmeen Almansour, Alfia Badiwalla
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引用次数: 0

摘要

由于设计上的限制,传统的数据库管理系统不适合处理不确定的数据。解决数据库不确定性的方法有很多,但往往过于简化和限制了可表示的不确定性。物联网、多媒体和社交媒体等技术带来的数据快速增长,导致了大量多样化的数据,被称为大数据,分为结构化、半结构化和非结构化类型。应对大数据挑战的“Vs模型”包含了体量、速度和多样性维度。它旨在收集变量信息,以便了解因果关系并作出明智的决定。大数据提供了竞争优势:智能决策(69%)、运营控制(54%)、客户洞察(52%)和成本削减(47%)。这项研究研究了大数据管理和云计算,其中数据和应用程序通过互联网访问,节省全球资源。云的简单性和强大功能为任务和存储提供了便利。风险包括破产或数据泄露,但云计算对于保存大数据仍然很有价值。大数据价值创造的关键因素包括将IT成本转化为资产,并将大数据成果与绩效联系起来。这篇摘要总结了对传统局限性、大数据本质、云潜力和价值创造细微差别的探索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data Management and Analytics as a Cloud Service
Traditional database management systems are inadequate for handling uncertain data due to design limitations. Various methods address database uncertainty, often oversimplifying and restricting representable uncertainties. Rapid data growth from technologies like IoT, multimedia, and social media has led to massive diverse data, known as big data, categorized into structured, semi-structured, and unstructured types. Coping with big data's challenges is encapsulated in the "Vs Model" with volume, velocity, and variety dimensions. It aims to gather variable information for causal understanding and informed decisions. Big data offers competitive advantages: smart decisions (69%), operational control (54%), customer insights (52%), and cost cuts (47%). This research studies big data management and cloud computing, where data and apps are accessed via the internet, saving resources globally. Cloud's simplicity and power facilitate tasks and storage. Risks include bankruptcy or breaches, yet cloud remains valuable for preserving big data. Vital factors in big data's value creation involve converting IT costs to assets and connecting big data outcomes to performance. This abstract summarizes exploration of traditional limitations, big data's essence, cloud's potential, and value creation nuances.
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