April 19, 2015

The business architect role and the enterprise architecture of tommorrow
To sum up, this enterprise business architect should operate higher up in the enterprise hierarchy to cover the business architecture and integrate it with the technology architecture. He will ensure that it is the full blueprint of the enterprise that it is delivered rather than the IT blueprint. And he will make sure that the audience is the whole enterprise rather than IT. This blueprint would enable stakeholders model own parts with same conventions and constraints in the enterprise wide context. This would unite the enterprise in one coherent operation and development effort. The EA would be the collective cross enterprise design where everybody contributes to the same plan and goals, in synchronization.

The Value of Data Platform-as-a-Service (dPaaS)
dPaaS provides enterprise-class scalability enabling users to work with rapidly-growing and increasingly complex data sets, including big data. Users have the flexibility to deploy any analytics tool on top of the platform to facilitate analyses in different environments and scenarios. The platform provides data stewards full transparency and control over data to ensure adherence with GRC (governance, regulatory, compliance) programs. dPaaS allows enterprises to reduce the burden of maintenance requirements for hardware and software. Companies can shift IT budgets from capex to more predictable opex, while freeing up IT teams to work on higher-return projects using market-leading technologies in collaboration with business units.

5 Unusual Ways Businesses Are Using Big Data
Big data is where it’s at. At least, that’s what we’ve been told. So it should come as no surprise that businesses are busy imagining ways they can take advantage of big data analytics to grow their companies. Many of these uses are fairly well documented, like improving marketing efforts, or gaining a better understanding of their customers, or even figuring out better ways to detect and prevent fraud. The most common big data use cases have become an important part of industries the world over, but big data can be used for much more than that. In fact, many companies out there have come up with creative and unusual uses for big data analytics, showing just how versatile and helpful big data can be.

How a Toronto prof changed artificial intelligence
In quick succession, neural networks, rebranded as “deep learning,” began beating traditional AI in every critical task: recognizing speech, characterizing images, generating natural, readable sentences. Google, Facebook, Microsoft and nearly every other technology giant have embarked on a deep learning gold rush, competing for the world’s tiny clutch of experts. Deep learning startups, seeded by hundreds of millions in venture capital, are mushrooming. Hinton now spend three-quarters of his time at Google and the rest at U of T. Machine learning theories he always knew would work are not only being validated but are finding their way into applications used by millions. At 67, when he might be winding down a long and distinguished career, he is just now entering its most exciting phase.

6 Wearables That Will Enhance The Wearable Revolution In 2015
The hearing aids continuously scan the acoustic environment and activate the most optimal settings for that particular listening situation. For example, if you are at a noisy family gathering, the smart hearing aids hone in on speech coming from the front while softening speech and noise from other directions. Later, if you are out walking the dog, they automatically adjust so you can enjoy the sounds of nature. ... The FitLinxx AmpStrip is a thin, waterproof device that tracks heart rate and activity around the clock with accuracy – all within a device as discrete and comfortable as a Band-Aid. It can be comfortably worn all day, every day. It easily sticks to your torso and automatically tracks heart rate, activity, exercise load, skin temperature and posture.

10 reasons to buy a Windows tablet for work instead of an iPad or Android
Tablets are going to work instead of laptops in some cases or to augment them in others. They can do a lot in the enterprise, some more than others. While the iPad and Android tablets are capable workmates, the tablets of choice are those running Windows. Windows has enjoyed a long reign as king of the workplace and that hasn't changed. There are a number of solid reasons why that is, and these reasons contribute to making Windows tablets the choice to take to work. ... Since Windows tablets provide more options to the enterprise when it comes to accessories, there is more cost flexibility. Also, business professionals will benefit from the app selection and the wide range of accessories.

Podcast: How to Architect for IoT
Some excerpts of this Podcast - IoT data is messy. Devices get cut off in mid-transition. How do you detect this–and clean it up–as data arrives?; IoT data is of incredibly high volume. By 2020, we will have 4x more sensor and IoT data than enterprise data. We already get more data today from sensors than we do from PCs. How do we scale to consume and use this. In addition, connected devices are not always smart or fault-tolerant. How do you ensure you are always ready to catch all that data; IoT and sensor and of itself is not terribly useful. It is rarely in a format that an analyst would even be able to read. It would be incredibly wasteful to store all this as-is in a business warehouse, DropBox repo, etc.

Digital Reasoning Goes Cognitive: CEO Tim Estes on Text, Knowledge, and Technology
Tim Estes founded Digital Reasoning in 2000, focusing first on military/intelligence applications and, in recent years, on financial markets and clinical medicine. Insight in these domains requires synthesis of facts from disparate sources. Context is key. The company sees its capabilities mix as providing a distinctive interpretive edge in a complex world, as will become clear as you read Tim's responses in an interview I conducted in March, to provide material for my recent Text Analytics 2015 state-of-the-industry article. Digital Reasoning has, in the past, identified as a text analytics company. Maybe not so much any more.

BI Industry Going Through Midlife Crisis
Seriously all the chatter about old slow BI approaches being left behind for rapid data discovery with little governance, one version of the truth being tossed to the wind in a new BI world being driven by the business, and even a short opening keynote flick created by the Gartner team showing a middle aged woman leaving her husband, tired of waiting, disappointed by empty promises, etc. did send a message and a warning signal. ... Data discovery tools are becoming totally irresistible to the business because they are fast, easy to use and visually drop-dead gorgeous. However, I can’t help but think a bit more BI sanity may return in a few years after the business realizes there is much more to a successful BI implementation than quickly connecting to data and creating pretty charts.

A Tester’s Perspective on Agile Snags
The true agile QA is also often responsible for non-unit-test tools, test environments, and test data. People in this role will find themselves weighing conflicting choices. The choices resemble those in non-agile projects, but the short timescales of an agile project make the problems particularly acute. The responsibility for test management is often delegated to one or two members of an agile team, rather than taken on by the team as a whole. Although working in agile keeps you on your toes, distributed responsibilities and better time management makes your work easier as well as efficient. Estimations also challenge agile testers.

Quote for the day

"I believe you have to be willing to be misunderstood if you're going to innovate." -- Jeff Bezos

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