Not very long ago, it would have been almost inconceivable to consider a new large-scale data analysis project in which the open source Apache Hadoop did not play a pivotal role.
Every Hadoop blog post needs a picture of an elephant. (Source: Paul Miller)
Then, as so often happens, the gushing enthusiasm became more nuanced. Hadoop, some began (wrongly) to mutter, was "just about MapReduce." Hadoop, others (not always correctly) suggested, was "slow."
Then newer tools came along. Hadoop, a growing cacophony (innacurately) trumpeted, was "not as good as Spark."
But, in the real world, Hadoop continues to be great at what it's good at. It's just not good at everything people tried throwing in its direction. We really shouldn't be surprised by this. And yet, it seems, so many of us are.
For CIOs asked to drive new programmes of work in which big data plays a part (and few are not), the competing claims in this space are both unhelpful and confusing. Hadoop and Spark are not, despite some suggestions, directly equivalent. In many cases, asking "Hadoop or Spark" is simply the wrong question.
In the world of CMOS semiconductor process, the fundamental heartbeat that drives the continuing evolution of all the devices and computers we use and governs at a fundamantal level hte services we can layer on top of them is the continual shrinkage of the transistors we build upon, and we are used to the regular cadence of miniaturization, generally led by Intel, as we progress from one generation to the next. 32nm logic is so old-fashioned, 22nm parts are in volume production across the entire CPU spectrum, 14 nm parts have started to appear, and the rumor mill is active with reports of initial shipments of 10 nm parts in mid-2016. But there is a collective nervousness about the transition to 7 nm, the next step in the industry process roadmap, with industry leader Intel commenting at the recent 2015 International Solid State Circuit conference that it may have to move away from conventional silicon materials for the transition to 7 nm parts, and that there were many obstacles to mass production beyond the 10 nm threshold.
But there are other players in the game, and some of them are anxious to demonstrate that Intel may not have the commanding lead that many observers assume they have. In a surprise move that hints at the future of some of its own products and that will certainly galvanize both partners and competitors, IBM, discounted by many as a spent force in the semiconductor world with its recent divestiture of its manufacturing business, has just made a real jaw-dropper of an announcement – the existence of working 7nm semiconductors.
There’s no other way to slice it: competition for digital audiences is brutal. Intolerance for poor performance and disengaging experiences drives customers to competitor’s sites more quickly and more permanently than any time in history. Users increasingly demand digital experiences that personalize to their immediate needs and adapt to the current context, not treat them as a market or demographic segment.
In recently published research, we found that even as expectations soar, enterprises are personalizing with methods that are too unsophisticated, too opaque, or too convoluted to meet the complexity and mutability needed to serve individuals. Persona-based segmentation is too simplistic to meet current, much less future, customer expectations. Some solutions provide predictive analytics capabilities but are limited to a few algorithms or black-box methods (e.g. neural networks) are not easily adaptable to new data or scenarios. Those that rely heavily on rules have become morasses, some customers needing to manage and maintain hundreds or thousands of rules to guide digital experiences.
This Forum will help you identify brand new software opportunities and run with them. It will hit on the must-have competencies that will empower application development and delivery leaders to execute on their company’s engagement strategies. This includes accelerating development processes, creating digital experiences, reaching mobile customers, and exploiting analytics and big data. Forrester analysts will deliver forward-thinking content while industry specialists – from companies such as McDonald’s, Mastercard, and GE Capital - will provide insight into some real and revolutionary new business approaches that are relevant to you right now.
Tencent’s news portal is one of the largest online news portals in China, with more than 25 channels covering all types of news. Tencent faces fierce competition, which it intends to combat by building its analytics competency. With the eyes of millions of Chinese soccer fans on the World Cup, Tencent has a chance to better target its news and reports by using social analytics — which the news portal did by launching a mini-site of World Cup 2014 coverage. More than 50 advertisers showed interest in the World Cup site, thinking that it would differentiate Tencent’s news offerings and draw more traffic. And they were right: The site got more than 3 million hits in the first week of the Cup.
Tencent now has the first social analytics website for sports in China. Supported by IBM’s Social Analytics engine and hosted in its SoftLayer data center in Hong Kong, the site aggregates data from most leading Chinese social platforms including Qzone, Renren, Sina Weibo, and Tencent Weibo. Full coverage of these social platforms can help Chinese businesses get a fuller picture of customers to better personalize and target offers. Tencent’s news editors also have a separate social analytics tool to find buzzwords or popular terms on social platforms and highlight these attention-getting phrases in their titles and articles.
This investment is delivering two major benefits to Tencent: