Alex Woodie：2019大資料預測

“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，法國詩人保羅·瓦勒裡(Paul Valery)曾寫道:“明日非同往昔。”對於始於20世紀中期的大資料趨勢來說，這句話同樣適用。如今的我們並不像多數人曾經設想的那樣，但在很多方面，未來要比現在許多人想象的更有趣。

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.

隨著新年開啟，我們邁向了新的征程，這是個推陳出新的最佳時機。Datanami特此為來自大資料、分析以及IT行業的預言家們提供了暢所欲言的平臺，讓我們來聽聽他們有何高見吧。

1

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大資料服務公司創始人兼執行長Ashish Thusoo表示：“毫無疑問，商業智慧和資料分析解決方案的投資將在2019年持續增長。”

【註釋】Qubole，創立於2012年，是一家基於雲端提供大資料DaaS服務的大資料開發公司。Qubole基於真正的自動擴充套件Hadoop叢集，從而使客戶能夠在雲端整合分析大資料。

“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，焦點在哪裡還不得而知。我預計，隨著企業利用實時資訊在客服、營銷、欺詐檢測和推銷等領域做出智慧決策的嘗試越來越多，流媒體資料分析將出現增長。隨著“資料民主化”的持續推進，資料分析也將出現增長。

2

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年是資料編錄之年”Alation公司宣稱，編錄資料這一趨勢沒有減弱的跡象，因為各家集團仍在努力盤存其資料資產，以便實現資料貨幣化和執行標準。隨著2019年正式開始，請在您的目錄中為特定型別的資料——行為後設資料留出空間。

【註釋】Alation，創立於2012年，是一家企業資料編錄服務提供商。他們提供了允許企業利用軟體為其資料提供單一訪問通道的軟體，幫助企業資料庫建立索引、商業智慧工具以及檔案系統，以簡化資料搜尋，也會自動爬取，解析和索引所有資料和資料的使用日誌。

“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.”

“這些資料分析可以被挖掘出來，以便人們更好地瞭解資料使用情況和有用程度，”Alation的聯合創始人、設計與戰略行動副總裁亞倫·卡爾布(Aaron Kalb)寫道。這與20年前推動谷歌搜尋排名的觀點是一樣的：網頁內容對其實用性的預測性較差，不如其他頁面(由其他人建立)連結到它的頻率高。隨著ML/AI（機器學習/人工智慧）的熱度持續減弱，我們將看到企業對這類影響驅動技術和行為後設資料產生濃厚的興趣。

3

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

Lexalytics的執行長傑夫•卡特林(Jeff Catlin)表示，儘管人工智慧和機器學習取得了進展，但我們仍不會擁有自動駕駛汽車。

【註釋】Lexalytics，文字分析開發商。其文字分析平臺可將數十億個非結構化資料和線上資訊轉換為對公司的可行性見解。

“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.”

卡特林寫道：“自動駕駛汽車正變得越來越好，好到足以讓人們放心乘坐著自動駕駛的雛形汽車行駛在加州、新加坡甚至西澳大利亞的道路上。儘管人類在絕大多數涉及自動駕駛汽車的交通事故中有過錯，自動駕駛汽車仍有一些亟待解決的問題——從雪天情況下識別車道標誌，到判斷是該救行人還是該救司機，再到在路上偵測袋鼠的出出沒……這項技術還沒有完全智慧到可以在交通過程中自行判斷需要做出的決定。”

4

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.

隱私問題將成為國家層面的頭等大事。華盛頓特區Immuta的工作人員說，該公司開發的軟體旨在提高人工智慧的隱私。

【註釋】Immuta，美國資料服務提供商，成立於 2014 年。他們致力於為資料管理員提供高效的資料隱私保護和管理服務，值得一提的是，Immuta 軟體的相容性非常好，可以部署在任何基礎設施上，無論是現場伺服器配置，還是在共有云或私有云端應用，甚至兩者混搭使用。

“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.”

“我們預計隱私問題在新的一年裡將變得越來越重要，這突顯出美國目前正在努力建立一個統一的國家隱私標準。考慮到歐盟通用資料保護條例（GDPR）對美國和全球公司運營方式的影響，雖然不至於讓所有公司措手不及，但會增加現有及或將產生的隱私問題對企業底線的影響。”

5

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的產品管理高階顧問阿德里安•莫爾(Adrian Moir)預測，我們甚至可以見證新的資料隱私條例擬議和頒佈。

【註釋】Quest Software，成立於1987年，是業界領先的應用管理解決方案供應商。致力於通過改善企業關鍵應用的效能和可用性，降低其執行成本，幫助 IT 專業人員高效率地完成關鍵業務資料和資料庫的管理工作。

“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寫道:“不管是否受到GDPR的影響(儘管大多數都受其影響)，企業都應該把它視作一個框架，對於那些構建流程的人來說，這是一個很好的起點。為資料的儲存和使用建立適當機制是相當重要的，如果我們想繼續保護個人資訊，我們需要更多監管。明年，相信我們會看到更多監管提案/或者實施，就像俄勒岡州參議員羅恩·懷登(Ron Wyden)最近提出的《消費者資料隱私法》(Consumer Data Privacy Act)。”

6

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，我們目睹了開源軟體供應商對雲端計算供應商的強烈反對。據Streamlio創始人、Twitter開源流媒體分析平臺Heron創始人卡蒂克•拉馬薩米(Karthik Ramasamy)預測，到2019年，這兩者之間的緊張關係將繼續升溫。

【註釋】Streamlio，一家美國初創公司，主要業務是提供下一代端到端的實時處理解決方案，致力於打造世界上第一個企業級的端到端實時資料處理平臺。

“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寫道:“越來越多的人擔心大型雲服務提供商會破壞開源社群和供應商，因為它們會推出自己的基於開源的封閉雲服務，而不會對這些開源社群做出任何貢獻。然而，在他們近期的舉動中，有跡象表明，大型供應商正在採取一種微妙的方式——某些情況下，他們一方面試圖利用開源來損害業內生態系統，而另一邊，他們卻支援著生機勃勃的開源生態系統。例如，最近釋出的Amazon管理流媒體可能會對Apache Kafka生態系統造成負面影響，儘管Amazon的開源平臺Firecracker旨在圍繞它本身建立一個開源社群和生態系統。這一（惡性）趨勢將在2019年及以後加速，因此這些公司在開源領域扮演‘好公民’角色的情況，值得我們關注。”

7

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.

亞馬遜一直在緩慢進軍其他領域，包括醫療保健、食品雜貨店和報紙。風險投資公司CRV的裡德•克里斯蒂安(Reid Christian)表示，如果亞馬遜在2019年進行一項影響企業軟體開發方式的大型收購，我們也不必感到驚訝。

【註釋】Charles River Ventures(CRV)，成立於1970年，是世界上歷史最悠久經營最成功的風險投資公司之一，其投資回報率一直位於風險投資公司前列。

“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.”

克里斯蒂安寫道:“我相信到2019年，亞馬遜將進行一項足以顛覆業界的重大收購，以增強亞馬遜的網路服務。如今，儲存和計算決策比以往任何時候都更多地掌握在開發人員手中，而非資訊長（CIO）。我相信亞馬遜將圍繞出色的開發人員體驗（DX）以超過10億美元進行收購，這意味著工作流和UI/UX是直觀而受消費者歡迎的。我預計亞馬遜希望在2019年擁有自己的重大時刻，就像微軟在2018年收購GitHub那樣。”

8

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的戰略顧問、董事會成員道格•希拉蕊(Doug Hillary)表示，（未來）分析有足夠的空間去影響日常業務的方方面面。

【註釋】Fractal Analytics組建於2000年，致力於為企業(消費品公司、零售商和金融機構)提供理解、預測和培養消費者行為，及改善市場營銷、定價、供應鏈、風險管控和索賠管理的工具。

“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.

他寫道:“企業將增加使用自然語言處理(NLP)、後端資料語音整合、分析和傳統CRM/ERP系統，為消費者和員工建立更加個性化和增強的客戶服務。”

9

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年對混合雲和多雲架構的推進將在2019年帶來更大的雲互操作性。

【註釋】IBM，創立於1911年，是全球最大的資訊科技和業務解決方案公司，擁有全球僱員 30多萬人，業務遍及160多個國家和地區。

“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方對Datanami表示:“雲端計算已經變得無處不在，但是為許多企業執行雲環境意味著要協調服務和硬體之間的窘境，它們並不能總是很好地協同工作。隨著80%以上的企業使用五家或更多不同的雲提供商，快速無縫移動資料的能力成為每一個IT部門的首要任務，尤其是在人工智慧和其他資料密集型工作負載變得越來越普遍的情況下。預計到2019年，儲存硬體和軟體將出現更多創新，以幫助企業更好地控制和管理雲足跡。”

10

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

NetApp首席戰略官阿蒂什•古德(Atish Gude)表示，預計雲端計算中的資料管理和人工智慧開發將變得更加自動化。

【註釋】NetApp，創立於1992年，是向目前的資料密集型企業提供統一儲存解決方案的居世界最前列的公司，其 Data ONTAP是全球首屈一指的儲存作業系統。

“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.

古德寫道:“人工智慧軟體和服務工具在雲端計算運用中的快速增長，將使人工智慧開發變得越來越容易。人工智慧應用程式將提供高效能和可伸縮性，無論是在內部還是外部，並支援多種資料訪問協議和不同的新資料格式。因此，支援AI工作負載的基礎設施也必須是快速、有彈性和自動化的。雖然人工智慧肯定會成為基礎設施供應商的下一個戰場，但大多數開發都將從雲端計算開始。”

11

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“首席極客”湯姆•拉洛克(Tom LaRock)冒了個險，宣稱2019年將是資料操作年。

【註釋】SolarWinds，創立於1999年，總部位於美國德州Austin，是一家IT基礎設施管理軟體的領先提供商，致力於為企業開發軟體以幫助管理其網路，系統和資訊科技基礎架構。

“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.”

“在當今日益數字化的世界中，資料不能被排除在敏捷決策過程之外，”拉洛克寫道。“事實上，我們預測2019年將是資料被認為是關鍵業務驅動因素的一年。資料文化將越來越多地應用到技術環境中，企業將成為資料驅動和資料優先。這種轉變也會帶來資料操作，因為傳統的管理員開始意識到，他們一次只能調一個頁面的優化索引的日子即將結束。”

12

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人工智慧和分析技術戰略主管扎卡里•賈維寧(Zachary Jarvinen)表示，這將是一個漫長的過程，但2019年終將會是人工智慧成為主流的一年。

【註釋】OpenText Corp，創立於1991年，加拿大最大軟體公司之一，也是全球知名的企業內容管理公司，專門研發企業使用的產品幫助管理大量內容。OpenText提供的軟體應用程式可為大型企業，政府機構和專業服務公司管理內容和非結構化資料。

“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.”

他寫道:“由來已久的企業人工智慧轉型之約將於2019年正式啟動。大多數企業已經達到了數字化成熟度，確保了大規模獲取高質量資料的能力。有了成熟的資料集，人工智慧供應商可以為特定的業務用例提供更低成本、更易使用的人工智慧工具。”

13

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產品管理總監阿莫德•古普塔(Amod Gupta)表示，在新興的無伺服器正規化中，用於構建應用程式的語言可能不是現在使用的語言。

【註釋】AppDynamics，成立於2008年，總部位於舊金山，是一家應用效能管理公司，曾連續三年保持Gatner應用效能管理產品領導者地位。

“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預言:“Java和.NET( Microsoft XML Web services 平臺)將被顛覆，成為無伺服器技術的事實語言。我們將看到越來越多的企業採用像Node這樣的新語言。用於在新技術(如無伺服器)上構建的Node.js和Python。到目前為止，Java和.NET企業佔據著主導地位，但新語言的足跡將增加很多。無伺服器功能,像Lambda函式，到目前為止主要用於開發和預生產環境，但我們可以看到他們今年轉向生產工作負載，尤其是Node.js和Python得到了更廣泛的採用。”

14

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

StorageCraft總裁道格拉斯•布羅克特(Douglas Brockett)表示，大資料意味著巨大的儲存需求，即使對於小公司來說，在2019年也是如此。

【註釋】StorageCraft，創立於2003年，是一家生產安全類的軟體產品，並致力於為虛擬和物理環境提供一流的備份、災難恢復、系統遷移和資料保護解決方案的公司。他們的產品為伺服器提供了高可用性，從而因停機產生的相關成本被降到了最低，通過資料保護、資料管理和業務連續性解決方案，使組織的關鍵資訊始終安全、可訪問和優化。

“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級的資料管理曾經只是大企業才會面臨的挑戰，”Brocket寫道，“根據國際資料公司IDC的資料，隨著資料增長10倍，Pb時代也將開始對中型企業造成衝擊。過去反常的情況將開始成為中小型企業和中型集團的常態。特別是中等規模的企業會發現，他們的IT架構根本無法隨著資料增長進行伸縮。與大型企業不同的是，他們既沒有技能也沒有預算來應對。將資料管理、保護和成本效益高的大規模儲存引入單一無阻環境的需求將會上升。”

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

聯想(Lenovo)總裁兼營運長吉安弗蘭科•蘭奇(Gianfranco Lanci)寫道：我們終將看到人工智慧對醫療保健的影響。

“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.”

蘭奇寫道:“人工智慧正在縮短急診候診室的時間，使遠端個性化醫療服務的提供和監控成為可能，提供關鍵硬體的可用性和可訪問性，甚至通過檢測和診斷腫瘤來解放醫生的時間。這些進步實際上是在拯救生命。”

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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.

你聽說過AI（人工智慧），但2019年將出現EI(倫理智慧)的崛起。Sumo Logic聯合創始人兼技術長克里斯蒂安•比德根(Christian Beedgen)表示。

【註釋】Sumo Logic，2010年在加州創立，是一家基於雲端計算的機器資料分析公司，專注於安全、操作和BI使用。它提供日誌管理和分析服務，利用機器生成的大資料提供實時It洞察，輔助企業對資料日誌進行管理和分析，並將分析結果應用到安全性威脅檢測、輔助理解相關事件等。

“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.

“我們對使用計算能力來增強人類決策能力的迷戀程度，可能已經超越了演算法方法本身的進步。事實上，人工智慧及其相關技術的成功應用仍侷限於影像識別和自然語言理解領域，在這些領域中，輸入/輸出場景可以合理構建，而且在2019年不會有太大變化。”

“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.”

他接著寫道：“不管收集了多少資料，要是認為任何企業都可以通過開啟人工智慧來變得成功或者更成功，這種想法是荒謬的。但支援人類和演算法的資料收集仍在繼續，並引發了嚴重的倫理問題，這是我們在未來幾年需要密切關注的問題。資料反映了人類，因此和人類一樣混亂，資料不能創造客觀性。眾所周知，資料和演算法使現有的偏見永久化，而充其量的自動化決策也難以解釋和證明。當我們陷入思考資料和演算法結合起來創造客觀真理的陷阱時，做出這樣的決定就更難了，隨著決策權的增強，責任也越來越大，越來越多的人將會對自己業務決策的影響負責。”

來源：資料觀

編譯：黃玉葉