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专家解读:2019年大数据行业预测2019-01-07 14:58:12 | 编辑:hely | 查看: | 评论:0

随着新年开启,我们迈向了新的征程,这是个推陈出新的最佳时机。Datanami特此为来自大数据、分析以及IT行业的预言家们提供了畅所欲言的平台,让我们来听听他们有何高见吧。

Industry Speaks: Big Data Prognostications for 2019

“The future isn’t what it used to be” the French poet Paul Valery wrote nine decades ago. The same could be said for the big data trend that began in the mid ’00s. We’re not where many thought we’d be, but the future, in many ways, turned out to be more interesting than many imagined.

90年前,法国诗人保罗·瓦勒里(Paul Valery)曾写道:“明日非同往昔。”对于始于20世纪中期的大数据趋势来说,这句话同样适用。如今的我们并不像多数人曾经设想的那样,但在很多方面,未来要比现在许多人想象的更有趣。

Now, as we kick start the New Year, it’s a good time to dust off the old crystal ball. Datanami has opened the floor to industry prognosticators from across the big data, analytics, and IT industries. Let’s hear what they have to say.

随着新年开启,我们迈向了新的征程,这是个推陈出新的最佳时机。Datanami特此为来自大数据、分析以及IT行业的预言家们提供了畅所欲言的平台,让我们来听听他们有何高见吧。

According to Ashish Thusoo, the founder and CEO of big data as a service firm Qubole, there’s no question that investments in business intelligence and data analytics solutions will continue to rise in 2019.

Qubole大数据服务公司创始人兼首席执行官Ashish Thusoo表示:“毫无疑问,商业智能和数据分析解决方案的投资将在2019年持续增长。”

【注释】:Qubole,创立于2012年,是一家基于云端提供大数据DaaS服务的大数据开发公司。Qubole基于真正的自动扩展Hadoop集群,从而使客户能够在云端整合分析大数据。

“The interesting question,” he writes, “is where will the focus be. I expect to see an uptick in streaming data analytics, as businesses try to leverage real-time information to make smart decisions in areas like customer support, marketing, fraud detection and upselling customers.” Also seeing growth will be ad hoc analytics as the “democratization of data” continues its relentless march.

“有趣的是,焦点在哪里还不得而知。我预计,随着企业利用实时信息在客服、营销、欺诈检测和推销等领域做出智能决策的尝试越来越多,流媒体数据分析将出现增长。随着“数据民主化”的持续推进,数据分析也将出现增长。

2018 was “the year of the data catalog,” declared Alation. That trend shows no sign of letting up, as organizations continue with the ongoing struggle to inventory their data assets for the purposes of monetization and regulatory compliance. As 2019 begins in earnest, keep room in your catalog for a particular type of data: behavioral metadata.

“2018年是数据编录之年”Alation公司宣称,编录数据这一趋势没有减弱的迹象,因为各家集团仍在努力盘存其数据资产,以便实现数据货币化和执行标准。随着2019年正式开始,请在您的目录中为特定类型的数据——行为元数据留出空间。

【注释】:Alation,创立于2012年,是一家企业数据编录服务提供商。他们提供了允许企业利用软件为其数据提供单一访问通道的软件,帮助企业数据库建立索引、商业智能工具以及文件系统,以简化数据搜索,也会自动爬取,解析和索引所有数据和数据的使用日志。

“Analysis of this data can be mined to better shine a spotlight on what’s used and what’s useful,” writes Aaron Kalb, the VP of design and strategic initiatives and co-founder of Alation. “This is the same insight that drove Google Search’s ranking prowess two decades ago: the content of a webpage was less predictive of its utility than how often other pages — built by other people — linked to it. As the ML/AI buzz continues to wear thin, we’ll see a strong appetite emerge for this type of impact-driven technology and behavioral metadata among organizations.”

“这些数据分析可以被挖掘出来,以便人们更好地了解数据使用情况和有用程度,”Alation的联合创始人、设计与战略行动副总裁亚伦·卡尔布(Aaron Kalb)写道。这与20年前推动谷歌搜索排名的观点是一样的:网页内容对其实用性的预测性较差,不如其他页面(由其他人创建)链接到它的频率高。随着ML/AI(机器学习/人工智能)的热度持续减弱,我们将看到企业对这类影响驱动技术和行为元数据产生浓厚的兴趣。

Despite the progress in AI and machine learning, we still won’t have self-driving cars, according to Lexalytics CEO Jeff Catlin.

Lexalytics的首席执行官杰夫•卡特林(Jeff Catlin)表示,尽管人工智能和机器学习取得了进展,但我们仍不会拥有自动驾驶汽车。

【注释】Lexalytics,文本分析开发商。其文本分析平台可将数十亿个非结构化数据和在线信息转换为对公司的可行性见解。

“Self-driving cars are getting better-0, enough that prototypes are trusted on the roads in California, Singapore and even Western Australia,” Catlin writes. “But while humans have been at fault in the overwhelming majority of accidents involving autonomous vehicles, self-driving cars still have some kinks to iron out. From ‘seeing’ lane markers in snowy conditions to making judgment calls about whether to save a pedestrian or a driver to detecting kangaroos on the road, the technology still hasn’t quite figured out how to handle all of the decision-making required when you’re in traffic.”

卡特林写道:“自动驾驶汽车正变得越来越好,好到足以让人们放心乘坐着自动驾驶的雏形汽车行驶在加州、新加坡甚至西澳大利亚的道路上。尽管人类在绝大多数涉及自动驾驶汽车的交通事故中有过错,自动驾驶汽车仍有一些亟待解决的问题——从雪天情况下识别车道标志,到判断是该救行人还是该救司机,再到在路上侦测袋鼠的出出没……这项技术还没有完全智能到可以在交通过程中自行判断需要做出的决定。”

Privacy will emerge as a top priority at the national level according to the folks at Immuta, a Wasington D.C.-area company that develops software aimed at boosting privacy in AI.

隐私问题将成为国家层面的头等大事。华盛顿特区Immuta的工作人员说,该公司开发的软件旨在提高人工智能的隐私。

【注释】Immuta,美国数据服务提供商,成立于 2014 年。他们致力于为数据管理员提供高效的数据隐私保护和管理服务,值得一提的是,Immuta 软件的兼容性非常好,可以部署在任何基础设施上,无论是现场服务器配置,还是在共有云或私有云端应用,甚至两者混搭使用。

“We expect privacy to increase in importance in the new year, highlighting current efforts to create a single, national privacy standard in the U.S.,” the company tells Datanami. “Given the impact the E.U.’s GDPR has had on how U.S. and global companies operate, this won’t catch all companies off guard, but it will increase the impacts that privacy issues have had – and will continue to have – on businesses’ bottom lines.”

“我们预计隐私问题在新的一年里将变得越来越重要,这突显出美国目前正在努力创建一个统一的国家隐私标准。考虑到欧盟通用数据保护条例(GDPR)对美国和全球公司运营方式的影响,虽然不至于让所有公司措手不及,但会增加现有及或将产生的隐私问题对企业底线的影响。”

We could even see new data privacy regulations proposed and enacted, foresees Adrian Moir, a senior consultant in product management at Quest Software.

Quest Software的产品管理高级顾问阿德里安•莫尔(Adrian Moir)预测,我们甚至可以见证新的数据隐私条例拟议和颁布。

【注释】Quest Software,成立于1987年,是业界领先的应用管理解决方案供应商。致力于通过改善企业关键应用的性能和可用性,降低其运行成本,帮助 IT 专业人员高效率地完成关键业务数据和数据库的管理工作。

“Whether affected by GDPR or not (most are), companies should be looking to it as a framework, it’s a good starting point for those building out their processes,” Moir writes. “It’s important to have something set-up for how data is kept and used. If we want to continue to have personal information protected, we will need to have more regulation. Next year, I believe we’ll see more regulation proposed and/or put in place, like the Consumer Data Privacy Act recently introduced by Oregon Sen. Ron Wyden.”

Moir写道:“不管是否受到GDPR的影响(尽管大多数都受其影响),企业都应该把它视作一个框架,对于那些构建流程的人来说,这是一个很好的起点。为数据的保存和使用建立适当机制是相当重要的,如果我们想继续保护个人信息,我们需要更多监管。明年,相信我们会看到更多监管提案/或者实施,就像俄勒冈州参议员罗恩·怀登(Ron Wyden)最近提出的《消费者数据隐私法》(Consumer Data Privacy Act)。”

In late 2018, we witnessed a backlash against cloud vendors by open source software vendors. In 2019, tensions between the two parties will continue to simmer, predicts, Karthik Ramasamy, the founder of Streamlio and creator of the open source Heron streaming analytics platform at Twitter.

在2018年底,我们目睹了开源软件供应商对云计算供应商的强烈反对。据Streamlio创始人、Twitter开源流媒体分析平台Heron创始人卡蒂克•拉马萨米(Karthik Ramasamy)预测,到2019年,这两者之间的紧张关系将继续升温。

【注释】Streamlio,一家美国初创公司,主要业务是提供下一代端到端的实时处理解决方案,致力于打造世界上第一个企业级的端到端实时数据处理平台。

“The fear has only grown that big cloud providers will undermine open source communities and vendors by launching their own closed cloud services based on open source without contributing back to those communities,” Ramasamy writes. “However, there are signs in these recent moves that big vendors are taking a nuanced approach—in some cases working to co-opt open source to the ecosystem’s detriment while in other cases supporting vibrant open source ecosystems. For instance, the recently released Amazon Managed Streaming for Kafka (Amazon MSK) is likely to have negative repercussions for the Apache Kafka ecosystem even as Amazon’s open source Firecracker aims to establish an open source community and ecosystem around it. This trend will accelerate in 2019 and beyond, and the extent to which these companies act as ‘good citizens’ within open source will bear watching.”

Ramasamy写道:“越来越多的人担心大型云服务提供商会破坏开源社区和供应商,因为它们会推出自己的基于开源的封闭云服务,而不会对这些开源社区做出任何贡献。然而,在他们近期的举动中,有迹象表明,大型供应商正在采取一种微妙的方式——某些情况下,他们一方面试图利用开源来损害业内生态系统,而另一边,他们却支持着生机勃勃的开源生态系统。例如,最近发布的Amazon管理流媒体可能会对Apache Kafka生态系统造成负面影响,尽管Amazon的开源平台Firecracker旨在围绕它本身建立一个开源社区和生态系统。这一(恶性)趋势将在2019年及以后加速,因此这些公司在开源领域扮演‘好公民’角色的情况,值得我们关注。”

Amazon has been slowly creeping into other ventures, including healthcare, grocery stores, and newspapers. Don’t be surprised if Amazon makes a big acquisition in 2019 that impacts how enterprise software is developed, says Reid Christian of CRV, a venture capital firm.

亚马逊一直在缓慢进军其他领域,包括医疗保健、食品杂货店和报纸。风险投资公司CRV的里德•克里斯蒂安(Reid Christian)表示,如果亚马逊在2019年进行一项影响企业软件开发方式的大型收购,我们也不必感到惊讶。

【注释】Charles River Ventures(CRV),成立于1970年,是世界上历史最悠久经营最成功的风险投资公司之一,其投资回报率一直位于风险投资公司前列。

“In 2019, I believe Amazon will make a big acquisition that will change the enterprise world and enhance Amazon Web Services,” Christian writes. “With storage and compute decisions today more than ever in the hands of developers instead of CIOs, I believe AWS will make >$1B acquisition centered around exceptional DX (developer experience), meaning workflows and UI/UX that are intuitive and consumer like. I expect Amazon will want to have a big enterprise moment in 2019, similar to what Microsoft had by acquiring GitHub in 2018.”

克里斯蒂安写道:“我相信到2019年,亚马逊将进行一项足以颠覆业界的重大收购,以增强亚马逊的网络服务。如今,存储和计算决策比以往任何时候都更多地掌握在开发人员手中,而非首席信息官(CIO)。我相信亚马逊将围绕出色的开发人员体验(DX)以超过10亿美元进行收购,这意味着工作流和UI/UX是直观而受消费者欢迎的。我预计亚马逊希望在2019年拥有自己的重大时刻,就像微软在2018年收购GitHub那样。”

There’s a lot of room for analytics to impact various aspects of everyday business, writes Doug Hillary, a strategic adviser and board member of Fractal Analytics.

Fractal analytics的战略顾问、董事会成员道格•希拉里(Doug Hillary)表示,(未来)分析有足够的空间去影响日常业务的方方面面。

【注释】Fractal Analytics组建于2000年,致力于为企业(消费品公司、零售商和金融机构)提供理解、预测和培养消费者行为,及改善市场营销、定价、供应链、风险管控和索赔管理的工具。

“Enterprises will increase the use of Natural Language Processing (NLP) and voice integration with back-end data, analytics and legacy CRM/ERP systems to create more personalized and enhanced customer service for consumers and employees,” he writes.

他写道:“企业将增加使用自然语言处理(NLP)、后端数据语音集成、分析和传统CRM/ERP系统,为消费者和员工创建更加个性化和增强的客户服务。”

The push to hybrid and multi-cloud architectures in 2018 will lead to greater cloud interoperability in 2019, according to the folks in IBM Systems.

IBM Systems的人士表示,2018年对混合云和多云架构的推进将在2019年带来更大的云互操作性。

【注释】IBM,创立于1911年,是全球最大的信息技术和业务解决方案公司,拥有全球雇员 30多万人,业务遍及160多个国家和地区。

“Cloud computing has become all but ubiquitous, but running a cloud environment for many enterprises means orchestrating a quagmire of services and hardware that don’t always play well together,” IBM Systems tells Datanami. “With more than 80% of enterprises using five or more different cloud providers, the ability to quickly and seamlessly move data becomes top of mind for any IT department, particularly as AI and other data-intensive workloads become increasingly common. In 2019, expect to see more innovations in storage hardware and software that help companies reign in and better manage their cloud footprint.”

IBM方对Datanami表示:“云计算已经变得无处不在,但是为许多企业运行云环境意味着要协调服务和硬件之间的窘境,它们并不能总是很好地协同工作。随着80%以上的企业使用五家或更多不同的云提供商,快速无缝移动数据的能力成为每一个IT部门的首要任务,尤其是在人工智能和其他数据密集型工作负载变得越来越普遍的情况下。预计到2019年,存储硬件和软件将出现更多创新,以帮助企业更好地控制和管理云足迹。”

Expect data management and AI development in the cloud to become more automated, writes Atish Gude, chief strategy officer at NetApp.

NetApp首席战略官阿蒂什•古德(Atish Gude)表示,预计云计算中的数据管理和人工智能开发将变得更加自动化。

【注释】NetApp,创立于1992年,是向目前的数据密集型企业提供统一存储解决方案的居世界最前列的公司,其 Data ONTAP是全球首屈一指的存储操作系统。

“A rapidly growing body of AI software and service tools – mostly in the cloud – will make AI development easier and easier,” Gude writes. “This will enable AI applications to deliver high performance and scalability, both on and off premises, and support multiple data access protocols and varied new data formats. Accordingly, the infrastructure supporting AI workloads will be also have to be fast, resilient, and automated. While AI will certainly become the next battleground for infrastructure vendors, most development will start in the cloud.

古德写道:“人工智能软件和服务工具在云计算运用中的快速增长,将使人工智能开发变得越来越容易。人工智能应用程序将提供高性能和可伸缩性,无论是在内部还是外部,并支持多种数据访问协议和不同的新数据格式。因此,支持AI工作负载的基础设施也必须是快速、有弹性和自动化的。虽然人工智能肯定会成为基础设施供应商的下一个战场,但大多数开发都将从云计算开始。”

Tom LaRock, a “head geek” at Solarwinds, has gone out on a limb and already declared that 2019 will be the year of DataOps.

Solarwinds公司的“首席极客”汤姆•拉洛克(Tom LaRock)冒了个险,宣称2019年将是数据操作年。

【注释】SolarWinds,创立于1999年,总部位于美国德州Austin,是一家IT基础设施管理软件的领先提供商,致力于为企业开发软件以帮助管理其网络,系统和信息技术基础架构。

“In today’s increasingly digital world, data cannot be excluded from the agile decision-making process,” LaRock writes. “In fact, we predict that 2019 will be the year that data is recognized as a key business driver. Data culture will become increasingly implemented into tech environments, and organizations will become data-driven and data-first. This shift will also give rise to DataOps as traditional admins start to understand that their days of tuning indexes are ending, one page at a time.”

“在当今日益数字化的世界中,数据不能被排除在敏捷决策过程之外,”拉洛克写道。“事实上,我们预测2019年将是数据被认为是关键业务驱动因素的一年。数据文化将越来越多地应用到技术环境中,企业将成为数据驱动和数据优先。这种转变也会带来数据操作,因为传统的管理员开始意识到,他们一次只能调一个页面的优化索引的日子即将结束。”

It’s been a long time coming, but 2019 will finally be the year that AI goes mainstream, according to Zachary Jarvinen, head of technology strategy for AI and analytics at OpenText.

OpenText人工智能和分析技术战略主管扎卡里•贾维宁(Zachary Jarvinen)表示,这将是一个漫长的过程,但2019年终将会是人工智能成为主流的一年。

【注释】OpenText Corp,创立于1991年,加拿大最大软件公司之一,也是全球知名的企业内容管理公司,专门研发企业使用的产品帮助管理大量内容。OpenText提供的软件应用程序可为大型企业,政府机构和专业服务公司管理内容和非结构化数据。

“The long-promised enterprise AI transformation is poised to begin in earnest in 2019,” he writes. “Most enterprises have reached a point of digital maturity, ensuring access to quality data at scale. With mature data sets, AI providers can offer lower cost, easier to use AI tools for specific business use cases.”

他写道:“由来已久的企业人工智能转型之约将于2019年正式启动。大多数企业已经达到了数字化成熟度,确保了大规模获取高质量数据的能力。有了成熟的数据集,人工智能供应商可以为特定的业务用例提供更低成本、更易使用的人工智能工具。”

The languages you use to build applications in the emerging serverless paradigm may not be the languages you use now, according to Amod Gupta, director of product management for AppDynamics.

AppDynamics产品管理总监阿莫德•古普塔(Amod Gupta)表示,在新兴的无服务器范式中,用于构建应用程序的语言可能不是现在使用的语言。

【注释】AppDynamics,成立于2008年,总部位于旧金山,是一家应用性能管理公司,曾连续三年保持Gatner应用性能管理产品领导者地位。

“Java and .NET will be overthrown as the de-facto languages for serverless technologies,” Gupta predicts. “We will see more and more enterprises adopt new languages like Node.js and Python for building on new technologies like serverless. So far, Java and .NET ruled the roost in enterprises, but the footprint of the new languages will increase by a lot. Serverless functions, like Lambda functions, have so far been predominantly used in development and pre-production environments, but we’ll see them move to production workloads this year, especially as Node.js and Python catch on in broader adoption.”

Gupta预言:“Java和.NET( Microsoft XML Web services 平台)将被颠覆,成为无服务器技术的事实语言。我们将看到越来越多的企业采用像Node这样的新语言。用于在新技术(如无服务器)上构建的Node.js和Python。到目前为止,Java和.NET企业占据着主导地位,但新语言的足迹将增加很多。无服务器功能,像Lambda函数,到目前为止主要用于开发和预生产环境,但我们可以看到他们今年转向生产工作负载,尤其是Node.js和Python得到了更广泛的采用。”

Big data means big storage requirements, even for small companies in 2019, according to Douglas Brockett, president of StorageCraft.

StorageCraft总裁道格拉斯•布罗克特(Douglas Brockett)表示,大数据意味着巨大的存储需求,即使对于小公司来说,在2019年也是如此。

【注释】StorageCraft,创立于2003年,是一家生产安全类的软件产品,并致力于为虚拟和物理环境提供一流的备份、灾难恢复、系统迁移和数据保护解决方案的公司。他们的产品为服务器提供了高可用性,从而因停机产生的相关成本被降到了最低,通过数据保护、数据管理和业务连续性解决方案,使组织的关键信息始终安全、可访问和优化。

“Petabyte-size data management used to be a challenge only large enterprises would face,” Brocket writes. “With data growing ten-fold – according to IDC – the petabyte era will start barreling down on mid-sized organizations too. What used to be an anomaly will start to become the norm for SMBs and mid-size organizations. Mid-sized organizations in particular will find their IT architectures simply can’t scale with their data growth. Unlike large enterprises, they won’t have the skills or budget to cope either. The demand to bring data management, protection and cost-effective scale out storage into a single frictionless environment will rise.”

“Pb级的数据管理曾经只是大企业才会面临的挑战,”Brocket写道,“根据国际数据公司IDC的数据,随着数据增长10倍,Pb时代也将开始对中型企业造成冲击。过去反常的情况将开始成为中小型企业和中型集团的常态。特别是中等规模的企业会发现,他们的IT架构根本无法随着数据增长进行伸缩。与大型企业不同的是,他们既没有技能也没有预算来应对。将数据管理、保护和成本效益高的大规模存储引入单一无阻环境的需求将会上升。”

We’ll finally start to see AI impacting healthcare, writes Gianfranco Lanci, president and COO of Lenovo.

联想(Lenovo)总裁兼首席运营官吉安弗兰科•兰奇(Gianfranco Lanci)写道:我们终将看到人工智能对医疗保健的影响。

“AI is reducing emergency waiting room times, enabling remote personalized health care delivery and monitoring, offering the availability and accessibility of critical hardware and even freeing up doctors’ time by detecting and diagnosing tumors,” Lanci writes. “These advancements are literally saving lives.”

兰奇写道:“人工智能正在缩短急诊候诊室的时间,使远程个性化医疗服务的提供和监控成为可能,提供关键硬件的可用性和可访问性,甚至通过检测和诊断肿瘤来解放医生的时间。这些进步实际上是在拯救生命。”

You’ve heard of AI. But 2019 will see the rise of EI, or ethical intelligence, according to Christian Beedgen, the co-founder and CTO of Sumo Logic.

你听说过AI(人工智能),但2019年将出现EI(伦理智能)的崛起。Sumo Logic联合创始人兼首席技术官克里斯蒂安•比德根(Christian Beedgen)表示。

【注释】Sumo Logic,2010年在加州创立,是一家基于云计算的机器数据分析公司,专注于安全、操作和BI使用。它提供日志管理和分析服务,利用机器生成的大数据提供实时It洞察,辅助企业对数据日志进行管理和分析,并将分析结果应用到安全性威胁检测、辅助理解相关事件等。

“Our fascination with the use of computing power to augment human decision-making has likely outgrown even the tremendous advances made in algorithmic approaches, ” Beedgen writes. “In reality, the successful use of AI and related techniques is still limited to areas around image recognition and natural language understanding, where input/output scenarios can be reasonably constructed, and that will not change drastically in 2019.

“我们对使用计算能力来增强人类决策能力的迷恋程度,可能已经超越了算法方法本身的进步。事实上,人工智能及其相关技术的成功应用仍局限于图像识别和自然语言理解领域,在这些领域中,输入/输出场景可以合理构建,而且在2019年不会有太大变化。”

“The idea that any business can ‘turn on AI’ to become successful or more successful is preposterous, no matter how much data is being collected,” he continues. “But the collection of data to support humans and algorithms continues and raises important ethical questions and is something we need to pay close attention to over the next few years. Data is human and therefore is just as messy as humans. Data does not create objectivity. It is well established that data and algorithms perpetuate existing biases and automated decisions are — at best — difficult to explain and justify. Appealing such decisions is even harder when we fall into the trap of thinking data and algorithms combine to create objective truth. With greater decision-making power comes much greater responsibility, and humans will increasingly be held accountable for the impact of decisions their business makes.”

他接着写道:“不管收集了多少数据,要是认为任何企业都可以通过开启人工智能来变得成功或者更成功,这种想法是荒谬的。但支持人类和算法的数据收集仍在继续,并引发了严重的伦理问题,这是我们在未来几年需要密切关注的问题。数据反映了人类,因此和人类一样混乱,数据不能创造客观性。众所周知,数据和算法使现有的偏见永久化,而充其量的自动化决策也难以解释和证明。当我们陷入思考数据和算法结合起来创造客观真理的陷阱时,做出这样的决定就更难了,随着决策权的增强,责任也越来越大,越来越多的人将会对自己业务决策的影响负责。”

注:《全球知名企业高管预测2019人工智能趋势》来源于Datanami 编译:黄玉叶

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