跨职能流程图
Big data encompasses the collection, storage, and analysis of massive stores of information. It’s helping users conduct research, create technological innovations, improve operational efficiency and drive organizations of all types toward their objectives. In conjunction with big data systems, enterprises are leveraging new technologies, such as advanced analytics, artificial intelligence (AI), the Internet of Things (IoT) and machine learning, to extract the value hidden in information. In the marketplace, these technologies are revolutionizing the way that enterprises conduct business.
大数据包括海量信息存储的收集，存储和分析。 它可以帮助用户进行研究，创新技术，提高运营效率，并推动各种类型的组织朝着自己的目标发展。 结合大数据系统，企业正在利用新技术（例如高级分析，人工智能（AI），物联网（IoT）和机器学习）来挖掘隐藏在信息中的价值。 在市场上，这些技术正在革新企业开展业务的方式。
As big data implementation expands, a relatively new management technique called cross-functional integration allows firms to make operational adjustments in an information-driven market where time-sensitive revelations emerge quickly. The new management paradigm allows various business units to collaborate efficiently and make better decisions. As big data implementations grow increasingly prominent among the world’s enterprises, more business leaders are implementing cross-functional organizational structures to make the most of the insights provided by big data reporting.
随着大数据实现的扩展， 称为跨功能集成的相对较新的管理技术使公司可以在信息驱动的市场中进行业务调整，在该市场中对时间敏感的信息Swift出现。 新的管理范例使各个业务部门可以有效地协作并做出更好的决策。 随着大数据实现在全球企业中日益重要，越来越多的可耐的星星正在实施跨职能的组织结构，以充分利用大数据报告提供的见解。
Big data will not, however, replace humans as strategic business advisors. Although there are astonishing new technologies that enterprise leaders can leverage to make informed decisions, there will always be a need for specialists who can interpret big data reports and determine what that information means for proprietors and organizations.
但是，大数据不会取代人类成为战略业务顾问。 尽管企业领导者可以利用惊人的新技术来做出明智的决策，但始终需要能够解释大数据报告并确定信息对所有者和组织意味着什么的专家。
变革性和破坏性技术 (A Transformative and Disruptive Technology)Enterprises use big data systems to implement informed marketing operations and better understand their clients and consumers. It’s a powerful resource for improving the productivity and prosperity of businesses. Resultingly, enterprises are aggressively investing in digital marketing and new technology infrastructures.
企业使用大数据系统实施明智的营销操作，并更好地了解其客户和消费者 。 它是提高企业生产力和繁荣的强大资源。 结果，企业正在积极投资于数字营销和新技术基础架构。
Big data systems have allowed enterprises to make meaningful use of data that they’ve collected and stored for years, and as firms gain experience in deriving value from data, they will undoubtedly invest in more advanced architectures to extract increased value from their proprietary information.
大数据系统使企业可以有意义地利用多年来收集和存储的数据，并且随着公司在从数据中获取价值的经验中积累，毫无疑问，他们将投资于更高级的架构，以从其专有信息中提取更多的价值。
Technology is changing how business leaders view the marketplace, and they are making adjustments accordingly. As a result, business leaders are rethinking management and organizational structures. The fast and powerful impact that big data has made across nearly all disciplines has left many business leaders unprepared to develop effective strategies to implement the technology. However, the innovation is at the forefront of thought of nearly all executives that seek new ways to improve the performance of their organizations.
技术正在改变企业领导者看待市场的方式，并相应地进行调整。 结果，企业领导者正在重新考虑管理和组织结构 。 大数据几乎涵盖了所有学科的快速而强大的影响，使许多业务领导者没有准备好制定有效的策略来实施该技术。 但是，创新是几乎所有寻求提高组织绩效新方法的高管思想的最前沿。
用数据指导船舶的新方法 (New Ways to Steer the Ship With Data)Because of big data systems, there’ve been enormous improvements in important fields, such as education, healthcare, finance, and marketing. Depending on the organizational mission and market share, enterprises leaders are investing in different technologies. For the most part, big data analysis is currently the primary driver of change, and most big data implementations have taken place in marketing and operational capacities.
由于采用了大数据系统，因此在教育，医疗保健，金融和市场营销等重要领域已取得了巨大的进步。 根据组织的使命和市场份额，企业领导者正在投资于不同的技术。 在大多数情况下，大数据分析当前是变更的主要驱动力，并且大多数大数据实现都发生在市场营销和运营能力方面。
However, as the big data market matures, enterprises leaders will discover new and powerful ways to leverage the technology. For instance, sentiment analysis is an emerging discipline within many fields and industries. Additionally, business leaders are making extensive use of predictive and structured data analysis to discover opportunities to improve operations and expand their clientele.
但是，随着大数据市场的成熟，企业领导者将发现利用该技术的新颖而强大的方法。 例如，情感分析是许多领域和行业中的新兴学科。 此外，企业领导者正在广泛使用预测性和结构化数据分析，以发现改善运营和扩展客户群的机会。
Automated video indexing is another relatively new and promising application for big data analytics systems. As more businesses and consumers create video content, big data will prove an invaluable resource for extracting meaningful information from video archives. Audio analytics and metadata content could further increase the value of this promising application.
自动化视频索引是大数据分析系统的另一个相对较新且前景广阔的应用程序。 随着越来越多的企业和消费者创建视频内容，大数据将成为从视频档案中提取有意义的信息的宝贵资源。 音频分析和元数据内容可以进一步增加这一有前途的应用程序的价值。
In the retail sector, enterprises are using camera footage to analyze in-store foot traffic. The proprietors use the technology to analyze characteristics such as consumer movement patterns, checkout flow, and traffic volume. The businesses use this information to make improvements in areas such as product placement, promotional campaigns and store layouts.
在零售领域，企业正在使用摄像机镜头来分析店内人流。 所有人使用该技术分析诸如消费者移动模式，结帐流程和交通量之类的特征。 企业使用此信息在产品放置，促销活动和商店布局等方面进行改进。
More advanced big data retail research involves the video analysis of group buying behaviour. This kind of study allows retailers to gather information about shopper buying patterns that go unnoticed at the cash register. Using video analytics, retail enterprises uncover missed opportunities by making a detailed analysis of this kind of group activity.
更高级的大数据零售研究涉及团购行为的视频分析。 这种研究使零售商能够收集有关收银机未注意到的购物者购买模式的信息。 零售企业使用视频分析，通过对此类团体活动进行详细分析，发现错过的机会。
Big data analysts are also making great strides in the analysis of data generated by social media users. This field brings together fields that appear unrelated at first glances, such as anthropology, computer science, economics, physics, psychology, and sociology.
大数据分析师还在社交媒体用户生成的数据分析方面取得了长足的进步。 该领域汇集了乍一看似乎无关的领域，例如人类学，计算机科学，经济学，物理学，心理学和社会学。
Big data is transforming the landscape of nearly all industries - and entire economies. Enterprise leaders will use the technology and other advanced analysis resources, as well as the IoT, to transform their brands, develop powerfully effective strategies and gain a competitive advantage in the marketplace. As time goes on, the early adopters of these technologies will reap rewards that will directly, and positively, impact their bottom lines.
大数据正在改变几乎所有行业以及整个经济的格局。 企业领导者将使用技术和其他高级分析资源以及IoT来改变其品牌，制定有力的有效策略并在市场上获得竞争优势。 随着时间的流逝，这些技术的早期采用者将获得回报，这些回报将直接且积极地影响其利润。
翻译自: https://www.experts-exchange.com/articles/32578/Big-Data-Optimization-Does-Cross-Functional-Integration-Hold-the-Key.html
跨职能流程图