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  • admin 9:51 am on February 9, 2018 Permalink
    Tags: , , , , Possible, , , valuedriven   

    A value-driven approach to telco customers, possible through advanced analytics 

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  • admin 9:51 am on November 21, 2015 Permalink
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    Will IoT & Analytics Really Make Full Automation Possible for Utility Power Networks? 

    There are now machines that have conquered the game of chess and starred on TV game shows. Soon we may even be able to chat and befriend them, a reality that perhaps isn’t too far off, when companies like Facebook are investing heavily in it to ensure secretive development on how its apps might be able to better help you find and communicate with your friends – automatically.

    What about in our Utility firms? Will we see machines roam more freely in the area of power network control? There is much debate around the level of automation that Internet of Things (IoT) based technologies, driven by analytics, will enable in network control, and over what timescales.

    But in reality, is full automation actually even possible?

    I’ve written in a previous blog post that today, analytics within the Utility networks business falls into three categories:

    • Distributed network solutions implemented on the network itself which have “productised” analytics at the heart of what they do;
    • Virtual control and monitoring solutions that continually run and assess the state of assets based on configurable analytics algorithms; and
    • Advanced analytics, and companies with “utilities big data” offers that integrate all data from across the Utility for analysis in conjunction with other relevant external data.

    Distributed network solutions” by their nature are automated, needing little human interaction. So this area is not contentious. But in “control and monitoring”, the idea of automation certainly is more contentious.

    So is full automation possible? In my opinion, “yes”, in theory at least. Although it may well be that automation is implemented very slowly given that installed physical infrastructure is a long way off managing and responding to the sophisticated control signals required, especially on low voltage networks.

    But we have to remember that culturally, this is a big deal. Network control is safety critical, and there will always be much that is unknown about how a power system might operate. full automation is never trusted enough to be implemented.

    Today virtual control and monitoring as described above is gaining traction, and helps engineers operate networks better. But this alone will not enable full automation. However, there is a trend emerging that challenges my own categorization of the use of analytics within the Utility networks business, which could lead us towards full automation. The three categories as I outline them above are merging.

    We are already seeing control and monitoring solutions emerging that can push analytics packets onto distributed assets real time, based on internal and external analytics triggers. Advanced analytics, and big data platforms are moving ever closer to real time, allowing more and more network data to be analysed in near real time to improve network operation, in combination with more parameters that a human could nominally apply manually.

    I believe that what we’re seeing is just the start. As the industry matures in its use of IoT, and analytics on the data from IoT, network analytics will only accelerate and become ever more intertwined. The way that analytics is performed today – separately – will become a thing of the past.

    Many in data and analytics talk about merging data from IT and OT systems for analytics purposes. Longer term, I see a single environment not only “doing analytics”, but gradually automating network operation, as well as the execution of many other businesses processes in the digital network business of the future. This is the latest potential of IoT for Utility power networks.

    Interested in discovering how IoT data can generate more value for your company when combined with business operations and human behavioural data? Read on.

    Iain Stewart is the principal utilities expert for Teradata in the EMEA region, with over 13 years of experience in utilities sector. Iain also has in depth experience of both smart metering and smart grids, including how these link to and support the wider sustainability agenda. Other areas of experience include renewable energy, and smarter cities. Connect with Iain Stewart on Linkedin.

    The post Will IoT & Analytics Really Make Full Automation Possible for Utility Power Networks? appeared first on International Blog.

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  • admin 9:51 am on April 14, 2015 Permalink
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    Is Time Travel Possible Without Big Data? 

    Is Time Travel possible? Many scientists, including Stephen Hawking, state that Time Travel is not possible for the simple reason that if it were possible, then we would have already seen all those time-travellers visiting us from the future. They are not here, so time travel is not possible.

    Source: http://www.insidescience.org/  

    In Science, as Karl Popper writes (The Logic of Scientific Discovery, 1934) “Logically, no number of positive outcomes at the level of experimental testing can confirm a scientific theory, but a single counter example is logically decisive”. In other words, lack of evidence is not a disproof.

    But Big Data is changing that.

    We are entering an era when so much data is available that failing to prove your claim with this data is taken as a proof of falsehood (while Popper says that having no evidence for a theory does not disprove it. So Popper would not accept that having seen no time travellers is a proof time travel is not possible).

    An example I read recently was for disproving homeopathy. Analysis of all available data on homeopathy result shows no difference between homeopathy and placebo. The headline was “homeopathic treatments have been proven to be completely useless” while the scientists used a more cautious language: “The available evidence is not compelling and fails to demonstrate that homeopathy is an effective treatment for any of the reported clinical conditions in humans”.

    Source: https://happyholistichealth.wordpress.com/tag/homeopathy-painkillers/

    To you and me both of these come to the same conclusion: even with lots of data, there is no evidence that homeopathy works; so you and I accept the inevitable conclusion: it doesn’t work (even though Karl Popper would have warned us that this is not a proof).

    Which brings me to the obvious question:

    What else is being disproved by lack of evidence?

    Source: http://5writers5novels5months.com/2013/01/

    For me (and I expect to see some heated argument on this), the next target is Astrology.

    Come on. Data Scientists have access to enough data about the world population to ascertain if it divides nicely into 12 types of people (one for each sign of the zodiac). Have you read any articles proving Astrology by Big Data analysis of the available data?

    No? OK, maybe you should accept that Astrology is not real.

    Similarly, have any fortune-tellers won the lottery recently?

    No? OK, maybe you should accept that they can’t tell the future with any precision.

    Numerology? Ditto.

    My point? With access to enough data and enough data scientists, the world is changing: lack of proof is becoming proof of falsehood. And Data Science has an important role to play.

    Ben Bor is a Senior Solutions Architect at Teradata ANZ, specialist in maximising the value of enterprise data. He gained international experience on projects in Europe, America, Asia and Australia. Ben has over 30 years’ experience in the IT industry. Prior to joining Teradata, Ben worked for international consultancies for about 15 years and for international banks before that. Connect with Ben Bor via Linkedin.

    The post Is Time Travel Possible Without Big Data? appeared first on International Blog.

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