1. Articles in category: Big Data and Analytics

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    1. How Banks Use Machine Learning to Know a Crook's Using Your Credit Card Details

      You’re sitting at home minding your own business when you get a call from your credit card’s fraud detection unit asking if you’ve just made a purchase at a department store in your city. It wasn’t you who bought expensive electronics using your credit card – in fact, it’s been in your pocket all afternoon. So how did the bank know to flag this single purchase as most likely fraudulent?

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    2. What are your APIs really worth?

      Since their debut 15 years ago, application programming interfaces (APIs) have grown into one of the foundational building blocks of modern application development. Now that we live in a world of microservices, how do you value the APIs that you're putting out there, whether it's the price of an external service or the worth of an internal one?

       

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    3. How to Jenga your way to an analytical enterprise

      An enterprisewide culture change towards a more data-driven, evidence-driven attitude, decisions and actions cannot be achieved simply through top down mandates and technology spends. One key strategy to achieving this change is to implement a series of user “advantages” that progressively reduce the time and effort required by users to be data-driven and analytical. Similar to the game of Jenga, where the intent is to build a high quality tower that increases in height while being structurally sound, enterprises should aim to enable a culture of analytics that is foundationally sound but flexible and extensible.

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    4. Do iPhones Dream Of Twitter Follows? What The AI Arms Race Means For Creative Technology

      You’re a tech giant that has built an artificial intelligence engine 5-7 years ahead of your competition that uses advanced machine learning to power many of your key products to the top of their class in functionality. What’s next? Share it with the entire internet. Last week Google open-sourced TensorFlow, the machine learning library that allows Google to recognize spoken…

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    5. Why overhyping data visualization will cause your BI project to fail

      Visualizing data has led to world-changing triumphs — from tracking epidemics to pinpointing weather impacts. Today, every company has adopted some form of data visualization to better understand their customers, service, and market. Yet, while both companies and users tend to emphasize data visualizations, they fail to recognize that visualizing data is an end result.

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    6. Google is open-sourcing its new machine learning system behind Google Photos

      Machine learning – systems to make computers work more like human brains – are behind some of Google’s best new products, including Google Now, Smart Reply in Inbox, and the crazy-good search in Google Photos (most of the time anyway). Now Google is revealing its newest machine learning system behind these technologies, and it’s called TensorFlow. Google says it’s ‘up to five times faster’ that its first-gen technology, so it’s been helping the company rapidly improve its products.

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    7. Thinking algorithm ready to take on conventional medicine

      Deep learning, a branch of artificial intelligence, could be in the medical mainstream in months. San Francisco software startup Enlitic is preparing to send software engineers to about 80 medical imaging centers in Australia and Asia. These “forward deployed engineers,” as company founder Jeremy Howard calls them, will install a deep-learning algorithm on IT systems, called Picture Archiving and Communications (PAC) systems.

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    8. Reinventing Analytics, Sideways

      The traditional way of doing analytics- with lots of separate, silo products for each aspect of analysis--is going away. New platforms allow new "sideways" combinations of features. Today if you want to fully leverage all of these different features across the organization, or as an individual, you typically have to install lots of different servers and interfaces. But what if you could do all of this with a single, blazingly-fast platform that you didn't even have to install? And you could provide a single interface that blended the best of all of these capabilities to reflect the new, more ...

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    9. The next information revolution will be 100 times bigger than the Internet

      Every day I see something I want to know more about, something I can experience at a deeper level, and share with my friends and family. I’m hardly alone in that; the average citizen of any connected country is an avid consumer, seeker, and sharer of information — driving over 5.7 billion Google searches each day. But what happens when you see something you can’t describe?

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    10. A hiring guide for building a data-driven culture

      We live in a world awash with data. From sensor data to website data, to fitness data, nearly every aspect of our lives is quantified. And digging into the numbers helps us better understand ourselves, our neighbors, and our world. For organizations, this can yield a huge competitive advantage — if they can see and understand their data. And that’s why many are adopting a culture of self-service analytics.

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    11. Big data is useless without algorithms, Gartner says

      Big data was so yesterday; it's all about algorithms today, according to Peter Sondergaard, Gartner Research senior vice president. Speaking at Gartner Symposium ITxpo 2015 on Tuesday morning, Sondergaard explained that key to helping companies grow the digital side of their business is to tap into algorithms. "Big data is not where the value is. Sure, data is necessary, but it's transient. By itself it will not be transformative. Your organisation may see you as the data-keeper, but anybody can gather data today, anybody can store it, and anybody can hire somebody to do data analysis -- no matter ...

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    12. Web personalization: How top companies go predictive to get results

      A few years ago, if the theme of “personalization” had emerged in your marketing circles, most industry people would have referred to Amazon as the gold standard. Predictive analytics looks at the future and can help determine a course of action — even without a marketer’s input. Marketers can now use tools to identify patterns found in historical data in order to inform or recommend future actions. Often, those recommendations can be automated, which means predictive analytics can scale efficiently. And these actions can be truly personalized for an exceptional customer experience.

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    13. Turning data scientists into action heroes: The rise of self-service Hadoop

      The unfortunate truth about data science professionals is that they spend a shockingly small amount of time actually exploring data. Instead, they are stuck devoting significant amounts of time wrangling data and pouring resources into the tedious act of prepping and managing it. Self-service Hadoop solutions simplify, streamline, and automate the steps needed to create a data exploration environment. 

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    14. Amazon’s new BI tool may hurt more of its partners

      Matt Wood, GM of Product Strategy for Amazon Web Services, chats with Network World about the company's QuickSight offering. The new offering gives AWS users business analytics from cloud-based services. AWS is a BI vendor now – just like Salesforce is with its Analytics cloud and Microsoft is with its PowerBI. It’s a natural progression for cloud vendors to offer analytics capabilities for data already stored on their platforms. It just may come at the expense of third-party ISVs who saw that opportunity first.

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    15. 5 Of The Best Social Media Tools That Help Newsrooms Find And Share Content

      As the march of technology (and the death of the traditional newsroom) continues, digital publishers and journalists (like us! ) need to continue to adapt to stay ahead of the game and successfully grow audiences. Here, we’ve got some of the best social media tools a digital newsroom can use to to find, source and promote stories by harnessing the power of the mass of publicly available data.

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    16. Dear enterprise: You are your algorithms, says Gartner

      Digital business and big data was a nice warm up act. Now your enterprise is all about the algorithms. "Algorithmic business is here," said Peter Sondergaard in his opening talk at the Gartner Symposium ITxpo. If you were to sum up the keynote, you might want to hire a few algorithm wonks. The challenge for CIOs is going to be to support bi-modal IT infrastructure for the analog model today and the digital focus tomorrow.

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    17. SwiftKey's latest keyboard is powered by a neural network

      A new SwiftKey keyboard hopes to serve you better typing suggestions by utilizing a miniaturized neural network. SwiftKey Neural does away with the company's tried-and-tested prediction engine in favor of a method that mimics the way the brain processes information. It's a model that's typically deployed on a grand scale for things like spam and phishing prevention in Gmail or image recognition, but very recent advancements have seen neural networks creep into phones through Google Translate, which uses one for offline text recognition. According to SwiftKey, this is the first time it's been used on a ...

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    18. 7 Intelligent Social Analytics Tools For The New Age

      The value of social media analytics was long before proven. But the extent to which it is influencing real-time business decisions has made all predictions look miniscule. Today, social insights has become one of the primary inputs into marketing and product strategy formulation. Dashboards by Radian6, Brandwatch and Sysomos have been ruling the monitoring space, but social analytics has evolved beyond monitoring in the last few years.

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    19. With air pollution app, Plume Labs wants to prove that big data and open government can save lives

      It would be harder to find buzzier buzzwords these days than “Big Data” and “Smart Cities” and “Open Government.” As more things get connected to the Internet, it creates the tantalizing potential to generate information that could help governments make cities more efficient, healthier, and safe. However, that potential has been slow to translate into things that actually have an impact on people’s day-to-day lives. Enter Plume Labs of Paris.

       

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    20. Google, NASA using quantum computing to push A.I., machine learning

      Google and NASA are continuing to test quantum computers and this week entered into a new agreement to work with a series of updated systems. D-Wave Systems, a quantum computing company based in Burnaby, British Columbia, announced this week that it had signed a deal to install a succession of D-Wave systems at NASA’s Ames Research Center in Moffett Field, California. NASA and Google on Wednesday also confirmed the deal.

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