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2014年1月18日 星期六

全球物聯網未來將啟動“工業物聯網” - 更將推向與人類互通全智物聯網( Welcome to the age of "internet Of Things" - A huge information system with predictive, sensing, understanding your speaking and from industrial internet to a future of information system can communicate with us )

The Chief Economist at General Electric, Marco Annunziata is a financial virtuoso with a passion for technology. His vision is "Machines increasingly communicate among themselves and with people. Mobile devices allow round-the-clock interconnectivity. Computers crunch terabytes of data. Such innovations have convinced economists from GE’s Marco Annunziata to Erik Brynjolfsson of MIT that the stage is set for a wave of productivity gains to rival the 10-year Internet boom that began in 1995." ( GE Marco Annunziata 預見未來 " 越來越多的機器之間及與人溝通。移動設備允許二十四小時的互聯互通。" 將延生『工業網際網路』),我更進一步預測人類將在 30 年形成『能與人類及機器互通全智互聯網』,網際網路及雲端智能就像空氣及我們心靈隨時跟我們及我們隨身機器做智能溝通;

Einstein said that "I never think about the future — it comes soon enough."

And he was right, of course. So today, I'm here to ask you to think of how the future is happening now. Over the past 200 years, the world has experienced two major waves of innovation. First, the Industrial Revolution brought us machines and factories, railways, electricity, air travel, and our lives have never been the same. Then the Internet revolution brought us computing power, data networks, unprecedented access to information and communication, and our lives have never been the same. ( 在過去的200年來,世界經歷了創新的兩大波。首先,工業革命給我們帶來的機器和工廠,鐵路,電力,航空旅行,讓我們的生活產生改變。那麼互聯網革命給我們帶來的計算能力,數據網絡,前所未有的獲取信息和溝通,讓我們的生活大改變 )

Now we are experiencing another metamorphic change: the industrial Internet. It brings together intelligent machines, advanced analytic, and the creativity of people at work. It's the marriage of minds and machines. And our lives will never be the same. ( 現在,我們正在經歷另一種巨烈質變化:工業互聯網。它匯集了智能機,先進的分析,以及人們在工作中的創造力。它是一種結合機器和人的思想。讓我們的生活和過去不一樣。)

In my current role, I see up close how technology is beginning to transform industrial sectors that play a huge role in our economy and in our lives: energy, aviation, transportation, health care. For an economist, this is highly unusual, and it's extremely exciting, because this is a transformation as powerful as the Industrial Revolution and more, and before the Industrial Revolution, there was no economic growth to speak of.

So what is this industrial Internet? Industrial machines are being equipped with a growing number of electronic sensors that allow them to see, hear, feel a lot more than ever before, generating prodigious amounts of data. Increasingly sophisticated analytic then sift through the data, providing insights that allow us to operate the machines in entirely new ways, a lot more efficiently. And not just individual machines, but fleets of locomotives, airplanes, entire systems like power grids, hospitals. It is asset optimization and system optimization. Of course, electronic sensors have been around for some time, but something has changed: a sharp decline in the cost of sensors and, thanks to advances in cloud computing, a rapid decrease in the cost of storing and processing data.


So we are moving to a world where the machines we work with are not just intelligent; they are brilliant. They are self-aware, they are predictive, reactive and social. It's jet engines, locomotives, gas turbines, medical devices, communicating seamlessly with each other and with us. It's a world where information itself becomes intelligent and comes to us automatically when we need it without having to look for it. We are beginning to deploy throughout the industrial system embedded virtualization, multi-core processor technology, advanced cloud-based communications, a new software-defined machine infrastructure which allows machine functionality to become virtualized in software, decoupling machine software from hardware, and allowing us to remotely and automatically monitor, manage and upgrade industrial assets. ( 因此,我們正在向一個世界裡,我們一起工作的機器不只是聰明,他們是輝煌的。它們有自我意識,它們能預測,它們據有反應性和社群性。)

Why does any of this matter at all? Well first of all, it's already allowing us to shift towards preventive, condition-based maintenance, which means fixing machines just before they break, without wasting time servicing them on a fixed schedule. And this, in turn, is pushing us towards zero unplanned downtime, which means there will be no more power outages, no more flight delays.

So let me give you a few examples of how these brilliant machines work, and some of the examples may seem trivial, some are clearly more profound, but all of them are going to have a very powerful impact.

Let's start with aviation. Today, 10 percent of all flights cancellations and delays are due to unscheduled maintenance events. Something goes wrong unexpectedly. This results in eight billion dollars in costs for the airline industry globally every year, not to mention the impact on all of us: stress, inconvenience, missed meetings as we sit helplessly in an airport terminal. So how can the industrial Internet help here? We've developed a preventive maintenance system which can be installed on any aircraft. It's self-learning and able to predict issues that a human operator would miss. The aircraft, while in flight, will communicate with technicians on the ground. By the time it lands, they will already know if anything needs to be serviced. Just in the U.S., a system like this can prevent over 60,000 delays and cancellations every year, helping seven million passengers get to their destinations on time.


Or take healthcare. Today, nurses spend an average of 21 minutes per shift looking for medical equipment. That seems trivial, but it's less time spent caring for patients. St. Luke's Medical Center in Houston, Texas, which has deployed industrial Internet technology to electronically monitor and MRIs to be analyzed in the cloud, developing better analytics at a lower cost. Imagine a patient who has suffered a severe trauma, and needs the attention of several specialists: a neurologist, a cardiologist, an orthopedic surgeon. If all of them can have instantaneous and simultaneous access to scans and images as they are taken, they will be able to deliver better healthcare faster. So all of this translates into better health outcomes, but it can also deliver substantial economic benefits. Just a one-percent reduction in existing inefficiencies could yield savings of over 60 billion dollars to the healthcare industry worldwide, and that is just a drop in the sea compared to what we need to do to make healthcare affordable on a sustainable basis.

connect patients, staff and medical equipment, has reduced bed turnaround times by nearly one hour. If you need surgery, one hour matters. It means more patients can be treated, more lives can be saved. Another medical center, in Washington state, is piloting an application that allows medical images from city scanners and

Similar advances are happening in energy, including renewable energy. Wind farms equipped with new remote monitorings and diagnostics that allow wind turbines to talk to each other and adjust the pitch of their blades in a coordinated way, depending on how the wind is blowing, can now produce electricity at a cost of less than five cents per kilowatt/hour. Ten years ago, that cost was 30 cents, six times as much. ( 類似的進步都發生在能源,包括可再生能源。配備了新的遙監控和診斷,使風力渦輪機相互交談並調整其葉片的槳距以協調的方式風力發電場,這取決於如何風在吹,現在可以產生電力在不到5美分成本每千瓦/小時。十年前,即成本為30美分,六倍之多。)

The list goes on, and it will grow fast, because industrial data are now growing exponentially. By 2020, they will account for over 50 percent of all digital information.

But this is not just about data, so let me switch gears and tell you how this is impacting already the jobs we do every day, because this new wave of innovation is bringing about new tools and applications that will allow us to collaborate in a smarter and faster way, making our jobs not just more efficient but more rewarding. Imagine a field engineer arriving at the wind farm with a handheld device telling her which turbines need servicing. She already has all the spare parts, because the problems were diagnosed in advanced. And if she faces an unexpected issue, the same handheld device will allow her to communicate with colleagues at the service center, let them see what she sees, transmit data that they can run through diagnostics, and they can stream videos that will guide her, step by step, through whatever complex procedure is needed to get the machines back up and running. And their interaction gets documented and stored in a searchable database.

Let's stop and think about this for a minute, because this is a very important point. This new wave of innovation is fundamentally changing the way we work. And I know that many of you will be concerned about the impact that innovation might have on jobs. Unemployment is already high, and there is always a fear that innovation will destroy jobs. And innovation is disruptive. But let me stress two things here. First, we've already lived through mechanization of agriculture, automation of industry, and employment has gone up, because innovation is fundamentally about growth. It makes products more affordable. It creates new demand, new jobs. Second, there is a concern that in the future, there will only be room for engineers, data scientists, and other highly-specialized workers. And believe me, as an economist, I am also scared. But think about it: Just as a child can easily figure out how to operate an iPad, so a new generation of mobile and intuitive industrial applications will make life easier for workers of all skill levels. The worker of the future will be more like Iron Man than the Charlie Chaplin of "Modern Times." And to be sure, new high-skilled jobs will be created: mechanical digital engineers who understand both the machines and the data; managers who understand their industry and the analytic and can reorganize the business to take full advantage of the technology. ( 這種新的創新浪潮正在從根本上改變我們的工作方式。我知道你們很多人會關注創新可能對就業的影響。失業率已經很高了,而且總有一種恐懼,創新將損害就業。創新是顛覆性的。但我想強調兩件事。首先,我們已經通過農業,工業自動化機械化生活,就業有所回升,因為創新是從根本上對增長。它使產品更加實惠。它創造了新的需求,新的就業機會。其次,有人擔心,在未來,只會有餘地工程師,數據科學家和其他高度專業化的工作人員。相信我,作為一個經濟學家,我也害怕。但仔細想想:就像一個孩子可以很容易地計算出如何操作一台iPad ,所以新一代的移動和直觀的工業應用將使生活更容易為所有技能水平的工人。未來的工人會更喜歡鋼鐵俠比的查理·卓別林“摩登時代”。並且可以肯定,新的高技能職位是:機械數字工程師誰了解雙方的機器和數據;誰了解他們的行業和分析,並可以重組業務,以充分利用該技術的管理人員。)

But now let's take a step back. Let's look at the big picture. There are people who argue that today's innovation is all about social media and silly games, with nowhere near the transformational power of the Industrial Revolution. They say that all the growth-enhancing innovations are behind us. And every time I hear this, I can't help thinking that even back in the Stone Age, there must have been a group of cavemen sitting around a fire one day looking very grumpy, and looking disapprovingly at another group of cavemen rolling a stone wheel up and down a hill, and saying to each other, "Yeah, this wheel thing, cool toy, sure, but compared to fire, it will have no impact. The big discoveries are all behind us." (Laughter)

This technological revolution is as inspiring and transformational as anything we have ever seen. Human creativity and innovation have always propelled us forward. They've created jobs. They've raised living standards. They've made our lives healthier and more rewarding. And the new wave of innovation which is beginning to sweep through industry is no different. In the U.S. alone, the industrial Internet could raise average income by 25 to 40 percent over the next 15 years, boosting growth to rates we haven't seen in a long time, and adding between 10 and 15 trillion dollars to global GDP. That is the size of the entire U.S. economy today.

But this is not a foregone conclusion. We are just at the beginning of this transformation, and there will be barriers to break, obstacles to overcome. We will need to invest in the new technologies. We will need to adapt organizations and managerial practices. We will need a robust cybersecurity approach that protects sensitive information and intellectual property and safeguards critical infrastructure from cyberattacks. And the education system will need to evolve to ensure students are equipped with the right skills. It's not going to be easy, but it is going to be worth it. The economic challenges facing us are hard, but when I walk the factory floor, and I see how humans and brilliant machines are becoming interconnected, and I see the difference this makes in a hospital, in an airport, in a power generation plant, I'm not just optimistic, I'm enthusiastic. This new technological revolution is upon us.

註: 根據分析之資料



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2013年12月26日 星期四

2020年,物聯網將連結300億台裝置產生1.9兆美元經濟總值 - 趨勢之微觀( Internet Connected Everything will create 1.9 billion value - detail watch )

研調:2020年,物聯網創造1.9兆美元附加價值

國際研究暨顧問機構 Gartner 表示,隨著數位世界的來臨,數位化浪潮將透過物聯網( Internet of Things )大幅改變科技市場的樣貌。儘管至2017年,歐洲、中東與非洲地區(EMEA)的IT支出將維持2.2%的年平均成長率,但包括人、物、地點以及系統的物聯網將創造出全新的市場與經濟型態。Gartner預測,物聯網所帶來的經濟附加總值將於2020年達1.9兆美元,且橫跨多種產業。其中率先導入的垂直市場為製造(15%)、醫療照護(15%)與保險(11%)。

Gartner 資深副總裁 Peter Sondergaard 表示,短期內,傳統IT市場的成長速度將不會再進一步增加,因此成長率的提升將來自於非傳統IT市場。雖然IT及電信合併市場將於2015年達到近4兆美元的規模,但至2020年,物聯網供應商所累積創造的營收預期每年將達3,090億美元。其中,半數的活動將為新創事業,而8成將投入於服務領域而非產品。就策略性而言,物聯網實為一個重要市場,其將急速發展且帶動營收及成本效益。

據Gartner表示,物聯網的範圍涵蓋硬體(即「物品」本身)、內嵌式軟體(在物品上執行並提供連網能力的軟體)、連網能力/通訊服務,以及與物品相關的資訊服務(包括根據使用習慣和感測器資料提供的服務)。提供此類硬體與服務的廠商統稱為「物聯網供應商」。
研究顯示,2009年,全球有25億台連網裝置,絕大部分為手機、PC以及平板。而到了2020年,全球將有超過300億台連網裝置,而且種類將更加多樣化(參見其上附圖)。

Sondergaard指出,物聯網將為所有企業組織及全球經濟創造出更大的經濟價值。舉例來說,製造業將受惠於生產數10億台裝置以及更有效率地追蹤原物料與零組件,而得以提升成本效益。在醫療照護方面,年長者專用的智慧拖鞋與其他穿戴式裝置內含感測器,可偵測失足以及各種醫療情況。若發生任何狀況,裝置會透過電子郵件或者簡訊通知醫師,如此可避免跌倒的情況並且省下昂貴的急診費用。另一個例子則是在有提供「按里程付費(pay as you drive, PAYD)」汽車保險的汽車內安裝感測器,將保險費與個人的風險狀況做連結。

Sondergaard表示,物聯網提供專為客戶打造的最佳化解決方案,以及創新的全新商業模式。這將使得公司改變單一定價(blank pricing)的模式,進而提供創造企業和客戶雙贏局面的客制化方案。

將實體與虛擬世界整合的「萬物聯網(Internet of Everything)」以及「力量的連結(Nexus of Forces)」,將帶領企業組織與其資訊長邁向一個兼容並蓄的數位未來。

萬物聯網將於下列三個層次上促使產業重新再造:商業流程、商業模式以及商機。Gartner研究副總裁Hung Le Hong表示,在第一個層次,數位科技不斷提升產品、服務及流程,讓客戶與用戶體驗企業內部運作和合作的方式。大眾仍依照平常的方式作業,但數位化讓用戶們做得更好,或者在業界開發出更好的產品。

當公司將產品及流程數位化之後,產業內就會出現嶄新的業務模式。隨著數位化促使產業於商業模式層次重新再造,Gartner分析師預期將會有更多轉型的變化出現。Le Hong舉例,運動品牌Nike搭配醫療領域的應用推出連網的運動衣及裝備;而Google則於無人駕駛載具領域有不錯表現。Le Hong表示,這些企業組織原本從未涉足其他產業,但現在他們正在塑造全新的自我。

數位再造的第三個層次來自於企業需要以前所未有的速度和靈活性競爭。Gartner稱其為「商機」(business moment)。

Le Hong以喜達屋(Starwood)、希爾頓(Hilton)以及凱悅(Hyatt)等大型連鎖飯店為例。這些公司過去一直在對抗電子商務時代第一波數位商業模式的競爭,如Hotels.com此類網站。然而,目前類似旅遊網站AirBnB的全新數位商業模式正促使這些連鎖飯店必須與數量更龐大的客房競爭。上述客房並不在其他的飯店內,而是在旅客自己的家中。

Le Hong表示,客房的來源和數量每晚皆不相同,形成一種商機層次的競爭。而『商機』可能來自不明地點,但卻越來越無所不在,且商機的產品、時間點和競爭者幾乎從不重複。

物聯網將創造數千萬種全新物品和感測器,全部都會產生即時資料。Gartner研究副總裁Nick Jones也說,資料即金錢。企業將需要巨量資料與儲存技術來蒐集、分析及儲存這麼龐大的資訊。不僅如此,要將資料轉化為金錢,企業和IT主管需要的是決策。因為他們將沒有時間或能力獨自應付所有決策,他們需要電腦運算的協助。電腦可根據資料和知識做出複雜的判斷,且能夠以母語來溝通其決策。想要以數位世界的速度成功,即必須交給電腦處理。

相較於企業一、兩年前的情況,大多數的資訊長在擁抱數位化方面都已有長足進展,但仍有近半數的資訊長表示他們尚未準備接受數位挑戰。

Gartner研究副總裁Dave Aron表示,既然數位化已蘊含在大眾所做的每一件事當中,每家企業都應有屬於自己的數位策略,不能流於平凡。數位化不是一種選項,不是一種附加品,也不是事後的想法。它是全新的現實,需要全方位的數位領袖。

IT in 2020: Internet of things, digital business enthusiasm abounds

The digitization of business and life will revamp the enterprise vendor pecking order — more like destroy it — create $1.9 trillion in economic value add via the Internet of things and lead to a digital workforce and smart machines that will replace 1 in 3 knowledge workers.

Welcome to Gartner's view of technology in 2020. The key theme is that every company will be a technology company. And Gartner research chief Peter Sondergaard went as far to say "every person is becoming a technology company" as the digital industrial economy kicks off.

Technology will be embedded into everything and be invisible. Naturally, this reality will grow data exponentially.

Sondergaard noted that there's a "crisis in IT leadership" as companies navigate digitization. He told CIOs that they need to create their company's digital story before the CEO creates roles for chief digital officers and digital strategists.

According to Sondergaard, virtual and physical will merge into one business reality. He said there will be "competing digital titles" as digitization takes hold, but people like chief digital officers will be extinct in 2020. These roles will implement change and then disappear.

The punch line with Sondergaard is that you'll need Gartner's research and services to lead your company to 2020 and digitization nirvana. Nevertheless, it's hard to argue with Gartner's take. The Internet of everything will mean companies will compete with a whole new set of players. Knowledge workers will be replaced by smart systems they trained. And tech vendors will face extinction on many fronts because they can't react and innovate fast enough.

Now you can quibble with Gartner's timeline — 2020 may be too soon —but CIOs should at least be able to see the digitization train coming down the tracks.

Let's look at some of Gartner's 2020 projections and do a reality check.
  • 20 percent of computers will learn not just process in 2017. This one doesn't seem like much of a stretch. Watson will be manning call centers in the not too distant future. 
  • By 2020, one in three knowledge workers will be replaced by enterprise owned smart machines they trained. Again, this prediction makes sense. IT is being automated and people will too.
  • The Internet of things will create economic value for all organizations and sectors and create an additional $1.9 trillion for the economy by 2020. I'm a bit skeptical about the timing more than the actual dollar amount. There are multiple technical issues — standards, interoperability — to work through. As for the dollar amount, these predictions really just require a number before a "trillion" to ramp excitement.
  • Digital time will go faster than your current IT vendors. Sondergaard said best of breed vendors have emerged because megavendors can't deliver value. This call is a no brainer. Your enterprise vendor today probably won't be in 7 years.
  • Two thirds of CIOs expect to change primary suppliers by 2017. I don't question the feeling that CIOs want to toss their vendors. My bet is lock-in will push out that supplier tossing timeline.
  • By 2017, 65 percent of data center capacity will be private, down from 80 percent today. Sondergaard's stat highlights the reality — enterprises aren't going cloud happy en masse. The run to the cloud may be slower — due to depreciation and other non-IT issues. It is safe to say that if you bought a server today it's going to be really hard to justify a purchase three years from now.
  • Companies will compete across industry borders. Sondergaard said "it's the death of the SIC codes." Think about how IBM and GE compete more and more everyday. UPS is a technology company just like Amazon is. The concept that companies will compete with rivals outside their industries isn't shocking, but in 2020 it's questionable whether every company will be information driven. Are we really going to see furniture companies do furniture as a service models?
  • In two years, the combined IT and telecom market will hit almost $4 trillion, or 5 percent of global GDP. A believable statistic — someone has to network the Internet of things.
  • By 2020, 30 billion things will be connected as every product more than $100 will be smart. I can see the reasoning as sensors are embedded everywhere. The things projection is largely a guess based on a growth rate. IDC also has its guess.
  • 3D printing will revolutionize the supply chain. This one is totally believable and on-demand parts will be critical for both new and mature products.


分析

2013年1月5日 星期六

2013 ~ 2015 年社群、雲端與巨量資料之發展潮流 ( 2013 ~ 2015 IT technology trend in big data )

2013年不容忽視的十大科技潮流 Gartner:行動裝置、社群、雲端與巨量資料

未來幾年科技業面臨的主要趨勢是什麼?哪些正在崛起的新勢力絕不容忽視?產業研究機構 Gartner 點名,行動裝置、社群、雲端與巨量資料等將主宰科技業走向。

周二(23日)Gartner分析師 David Cearley 在美國奧蘭多舉行的 SymposIUm/ITxpo 年度科技論壇上,依據未來三年的產業影響力,提出明年必須關注的十項科技趨勢。

面對滿堂科技業人士,Gartner 開宗明義指出,明年企業 IT 部門必須將雲端、社群、行動與資訊謹記在心。

首先入列的是,行動裝置即將進入戰國時代;預計到 2013 年行動電話將取代電腦成為民眾最主要上網裝置,而且 3 年內逾 8 成新銷售手機都將屬於智慧型等級;此外,估計 2015 年前平板佔整體電腦出貨就可增加至 50%,而微軟 Windows 8 將成為僅次於 Android 與 iOS 的第三大作業系統。

與此同時,隨著行動上網躍為主流,Gartner 也估計 HTML5 開發工具將更加普及,而向網路應用靠攏的長期趨勢也無可避免。

另一項要點也是目前正迅速發展的--雲端服務終究會取代電腦成為個人資訊的最佳儲存所;Gartner 強調,IT 產業正走向雲端、社群與行動的整合,其中雲端更扮演著聯繫網的關鍵角色。
Gigastone 個人雲產品, 得過2015精品獎
而在巨量資料(big data)與分析方面,Gartner 估計今年全球 IT 支出為 3.6 兆美元,明年將超過 3.7 兆美元,其中最主要成長動能將來自巨量資料。

Cearley 也不忘解釋,雖然社群不列在十項之列,但事實上它已深入科技的各個層面,整合並發展出新的運用及意涵。

Cearley 列出的 2013年十大策略性科技潮流包括:
  • 行動裝置戰爭
  • 行動應用與HTML5
  • 個人雲
  • 物聯網 (Internet of Things)
  • 混合 IT 與雲端運算
  • 策略性巨量資料
  • 可行動策略
  • 記憶體內運算
  • 整合生態系統
  • 企業應用程式商店
:巨量資料之大數據應用將大幅增加,個人混合雲會開始起來;整合生態系統之雲端運算及策略性巨量資料也將形成。

Big Data Revolution? ( 2013年雲端大數據之發展: 大數據革命?)
If you just invested a lot of money in a Big Data solution from any of the traditional BI vendors (Teradata, IBM, Oracle, SAS, EMC, HP, etc.) then you are likely to see a sub-optimal ROI in 2013.
一些創新會在2013年,這將改變大數據的價值指數。其他技術創新,只是在等待智能啟動,將其付諸很好地利用。 Several innovations will come in 2013 that will change the value of Big Data exponentially. Other technology innovations are just waiting for smart start-ups to put them into good use.
Real-Time Hadoop 即時 Hadoop
第一次重大創新將是谷歌 Dremel 的類似的解決方案,如 ImpalaDrill的來臨時期,等他們將允許大數據的即時查詢和開源服務。所以,你會得到一個優越的發售相比,什麼是目前免費提供。The first major innovation will be Google’s Dremel-like solutions coming of age like ImpalaDrill, etc. They will allow real-time queries on Big Data and be open source. So you will get a superior offering compared to what is currently available for free.
Cloud-Based Big Data Solutions ( 基於雲計算的大量數據解決方案 )
The absolute market leader is Amazon with EMR. Elastic Map Reduce is not so much about being able to run a Map Reduce operation in the Cloud but about paying for what you use and not more. The traditional BI vendors are still getting their head around a usage-based licensing for the Cloud. Except a lot of smart startups to come up with really innovative Big Data and Cloud solutions.
Big Data Appliances
你可以買一些真正昂貴的大數據設備,但在這裡破壞性的策略之公司都有可能改變市場。 GPU(圖形處理器)也相對便宜。堆棧到侍服器和使用 likeVirtual 的 OpenCL 的東西,使自己的GPU虛擬化集群解決方案。這些類型的自製GPU集群已經被用於安全大數據相關的工作。You can buy some really expensive Big Data Appliances but also here disruptive players are likely to change the market. GPUs are relatively cheap. Stack them into servers and use something likeVirtual OpenCL to make your own GPU virtualization cluster solution. These type of home-made GPU clusters are already being used for security Big Data related work.
同時也希望更多的硬件廠商,移動ARM處理器打包到侍服器裡。戴爾,惠普等已經在推出。想像一下,分佈式的 Map Reduce 的潛力..Also expect more hardware vendors to pack mobile ARM processors into server boxes. DellHP, etc. are already doing it. Imagine the potential for Distributed Map Reduce.
最後 Parallella 把一個16核心的超級計算機到每個人的手中,為99美元。其2013年的超級計算機面臨的挑戰是肯定的東西,保持你的眼睛。他們的產品路線會觸及 64和1000的核心版本。如果Adapteva 公司可以保持他們的承諾,並與Parallella充斥市場的預期Parallella集群,成為2013年大數據設備。Finally Parallella will put a 16-core supercomputer into everybody’s hands for $99. Their 2013 supercomputer challenge is definitely something to keep your eyes on. Their roadmap talks about 64 and 1000 core versions. If Adapteva can keep their promises and flood the market with Parallella’s then expect Parallella Clusters to be 2013 Big Data Appliance.
Distributed Machine Learning
Mahout is a cool project but Map Reduce might not be the best possible architecture to run iterative distributed backpropagation or any other machine learning algorithms. Jubatus looks promising. Also algorithm innovations like HogWild could really change the dynamics for efficient distributed machine learning. This space is definitely ready for more ground-breaking innovations in 2013.
Easier Big Data Tools
這仍然是一個大的白點在開源領域。有開源和易於使用的拖拉工具為大數據分析真的很讓人接收它。我們已經有了一些良好的商業的例子(Radoop= RapidMiner+Mahout,Tableau,Datameer等),但我們仍缺少良好的開源工具。This is still a big white spot in the Open Source field. Having Open Source and easy to use drag-and-drop tools for Big Data Analytics would really excel the adoption. We already have some good commercial examples (Radoop = RapidMiner + MahoutTableauDatameer, etc.) but we are missing good Open Source tools.


Intelligent Applications: The Big Data Theme for 2013 ( 智能應用:2013年巨資料的主題 )

我的預測是2013年的,有競爭力的優勢將轉化為企業使用複雜的巨資料分析的應用 - 創建一個新的品種智能應用程序My prediction for 2013 is that competitive advantage will translate into enterprises using sophisticated Big Data analytic to create a new breed of applications - Intelligent Applications.

“It’s more than just insights from MapReduce”, a CIO from a fortune 100 told me, “It’s about using data to make our customer touch points more engaging, more interactive, more intelligent.”

所以當你聽到關於“巨資料解決方案”,則需要翻譯成一類新的“智能應用”。在一天結束的時候,它不是關於人看透 Peta Byte的資料。它實際上是關於如何將巨資料轉化為收入(或利潤)。So when you hear about “Big Data solutions”, you need to translate that into a new category of “Intelligent Applications”. At the end of the day, it’s not about people pouring through petabytes of data. It’s actually about how one turns the data into revenue (or profits).

Morgan Stanley named the top ten as follows: ( 摩根士認為前十大應用如下:)
  • Healthcare ( 醫療保健 )
  • Entertainment ( 娛樂 )
  • Com/Media ( COM/媒體 )
  • Manufacturing ( 製造業 )
  • Financial ( 金融 )
  • Business Services ( 商業服務 )
  • Transportation ( 運輸 )
  • Web Tech ( 網絡技術 )
  • Distribution ( 行銷分配 )
  • Engineering ( 工程 )
Many have predicted which Industry is the most attractive (see McKinsey’s Quarterly for another). I personally like Ad-Tech and Financial Services for verticals….followed by Information Management , Health (if you can partner to speed up sales cycles), and Communications.

But what about market segments by technology?

我預測,數據分析服務(或簡稱作為作為巨資料服務(BDaaS))將有最高的增長(顯然是建立在它的成熟程度的收入基數較小)。商業智能服務是下一個高速增長的領域,需要更簡單的方法,提出和可視化數據,測井服務。I predict that Data Analytics as a Service (or also referred to as Big Data as a Service (BDaaS)) will have the highest growth (obviously building from a small base in revenue given its level of maturity). Business Intelligence as a Service is the next high-growth segment, given the need for easier ways to present and visualize data, followed by Logging as a Service.

But don’t take my word for this….my data comes from prominent research organizations. I’m just compiling and presenting their data in a slightly new way.

What challenges will end-user organizations struggle with the most in 2013?

End-users will continue to struggle with making sense out of the many technologies available. Is it EMC Greenplum connected to EMC Hadoop? Is it Cloudera Impala + Hadoop? Is it AsterData + Hortonworks? Is it MapR Hbase + HDFS? I think one thing is definite….you have lots of options.

The biggest problem will be whether they are actually satisfying the needs of the business problem. Here are my leading predictions for end-user organizations:

  • End users just want to solve problems, but will continue to fight IT over who owns the platform powering their much-needed data-driven applications
  • Ultimately, end-users will be forced to chase “shinny objects” because IT groups will persuade them to wait for the “technology bake-offs” around the Big Data platform soon to be launched (24 months from now)
  • In the end, many organizations will fail at creating value from Big Data due to a lack of focus on business problems, time-to-market, and in some cases the wrong technology choice
  • What are some of the key technologies that will dominate the Big Data market in 2013?
So many equate Big Data with Hadoop. But as you begin to see with announcements like Impala from Cloudera, it’s more than just Hadoop. It’s about servicing all the application response time requirements. It’s about volume, velocity, and variety but also time-to-value with your data analytic.

My prediction for 2013 is that you will need the following technology components:
  • Real-time stream processing
  • Ad-hoc near real-time analytics (see NoSQL and NewSQL data stores)
  • Batch Analytics
  • Not one, but all three!
What steps can customers take to maximize competitive advantage with Big Data in 2013?

Time to market 競爭優勢的所有。我毫不懷疑,全球2000強公司將在2013年推出自己的巨資料平台。問題是,當他們把這些平台推出,需要多長時間的時候到更多的收入,他們聘請 Accenture,CSC,Capgemini,IBM或想實現他們的巨資料之公司,能推出的智能應用程序嗎?Competitive advantage is ALL about time-to-market. I have no doubt that every Global 2000 company will launch their Big Data initiatives in 2013. The question is when they will turn those initiatives into additional revenue…how long will it take from the time that they hire Accenture, CSC, Capgemini, IBM or the like to implement their Big Data strategies, to launching an intelligent application? 
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