Emerging challenges in information management: A perpective from the industry

Girish Venkatachaliah
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Abstract

The digital ecosystem and information management are being hit by the perfect storm — the exponential growth of both structured and unstructured information, the astoundingly varied digital sources from social networks to the cars we drive, and the rising expectation and need for speedy decision making. Paradoxically, as the information grows, the ability to harness it intelligently is diminishing. It is further compounded by our difficulty in actually discovering the relevant piece of information needed to drive the decision in the context within the systemic constraints. The paper presentation will explore the challenges in the digital information management space with specific focus on analyzing, securing and harnessing the information, what needs to be done to foster the ecosystem, the challenges/gaps that exist, and the progress that is crying to be made in the coming decade. The paper will expound on the spectrum of complexities starting from the fundamental information extraction from data, and then discuss the approaches for synthesizing, standardizing and harmonizing noisy data to derive a holistic view. The paper will then elaborate ways of discovering information, and touch upon industry challenges in the space. The conclusion will highlight the emerging trends of gaining insights and intelligence, and being able to model and predict competitive behavior.
信息管理中的新挑战:来自行业的观点
数字生态系统和信息管理正受到一场完美风暴的冲击——结构化和非结构化信息的指数级增长,从社交网络到我们驾驶的汽车的数字来源的惊人变化,以及对快速决策的日益增长的期望和需求。矛盾的是,随着信息的增长,智能地利用它的能力正在减弱。我们在实际发现在系统约束的环境中驱动决策所需的相关信息方面的困难进一步加剧了这一点。论文将探讨数字信息管理领域的挑战,重点是分析、保护和利用信息,需要做些什么来培育生态系统,存在的挑战/差距,以及未来十年迫切需要取得的进展。本文将从数据的基本信息提取出发,阐述复杂性的频谱,然后讨论噪声数据的综合、标准化和协调方法,从而得出一个整体的观点。然后,本文将详细阐述发现信息的方法,并触及该领域的行业挑战。结论将强调获得洞察力和情报的新兴趋势,以及能够建模和预测竞争行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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