捷豹路虎利用图数据库度疫情难关

本次疫情对捷豹路虎的核心业务来说是一场巨大挑战，这包括了工厂停工两个月、半导体短缺以及供应和需求方面的严重挑战。但由于借助了先进的数据分析，这家英国跨国汽车公司不仅经受住了这场风暴，还比预期更精准地做到了，而且利润更高。

JLR’s 40-person data science and analytics team has developed an innovative forecasting engine atop a mixed proprietary/open source stack to the tune of £100 million in revenue during each of the past three years, with £2 million in profit directly attributed to JLR’s data team in 2020 — despite a disastrous global pandemic, says Harry Powell, director of data and analytics at JLR.

JLR的数据和分析总监Harry Powell表示，JLR有一个40人数据科学和分析团队，团队在一个混合专有开源堆栈之上开发了一个创新预测引擎，在过去三年中每年都有高达1亿英镑的收入，尽管这次的灾难性全球大流行，2020年里200万英镑的利润直接拜JLR数据团队所赐。

“One of the key parts of our strategy has been implementing graph technology in the business, and we’ve had some reasonably good results applying it to the supply chain,” says Powell, noting that JLR’s use of graph database technology from TigerGraph has been critical in reducing the automaker’s supply chain planning from three weeks to 45 minutes.

Powell表示，“我们战略的关键之一是在业务中落实图技术，我们将其用在供应链上，已经取得了一些相当好的结果。”他指出，JLR使用TigerGraph图数据库技术，这对于将该家汽车制造商的供应链规划可以从三周缩短到45分钟起到了至关重要的作用。

JLR now plans to deploy graph database technology to address quality improvement and pricing applications for its automobiles.

JLR现在计划进一步部署图数据库技术，用于解决旗下汽车的质量改进和定价应用。

As opposed to relational and non-SQL databases, graph databases detect, capture, and leverage connections among data stored or actively in use in business processes in real time, making them superior to relational databases when tackling challenges involving “incidental and unpredictable relationships,” says Carl Olafson, a research vice president at IDC.

IDC的研究副总裁Carl Olafson表示，相对于关系型数据库和非SQL数据库，图数据库可以进行实时检测、捕获及可以利用存储的数据或在业务流程中积极使用的数据之间的联系，这就使得图数据库在处理涉及“偶然和不可预测的关系”的挑战时比关系型数据库更优越。