Updates from September, 2015 Toggle Comment Threads | Keyboard Shortcuts

  • admin 9:47 am on September 27, 2015 Permalink
    Tags: , Churn, , , , Techniques   

    Analytic Techniques for Improving Loyalty and Reducing Churn 


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  • admin 9:54 am on September 26, 2015 Permalink
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    Teradata Database 15 


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  • admin 9:54 am on September 26, 2015 Permalink
    Tags: , , , , , WindUp.   

    The Apple Watch Is Just A Big Data Wind-Up. Right? 

    Lights! Camera! Action!

    The Apple Watch is launching amid much excitement, promising to change the way we generate and use data with a sweep of the hand. Okay, it’s not the first of its kind; we’ve seen smartwatches before – Samsung, Microsoft, even Swatch.

    But there’s nothing quite as moreish as a shiny new Apple.

    Portable good. Wearable better.

    That said, in spite of the hype and extraordinary market expectations – 360 million smartwatches by year 2020 – wearable technology is hardly a new concept. Product designers have been trying to integrate technology and clothing for years. In fact, in 2003, Burton and Apple developed the Burton Amp – a jacket that enabled switched-on snowboarders to control an iPod with a twitch of their sleeves.

    However, this less-niche, smartwatch revolution is likely to attract both sporty and non-sporty types. And if broad-brush appeal turns into sustainable sales, smartwatch sensors are going to transform us all into 24-hour transmitters. Which means big data changes all round.
    watch
    3 ways the Apple Watch could change Big Data

    1. An Apple-data deluge – say a third of iPhone owners buy an iWatch. Then 100 million sensors will be pumping out data, 24-7, from Apple people alone.
    1. A new app market – the next wave of apps will be designed for smartwatches. Accelerometers, thermometers, barometers, and altimeters – a handful of the hundreds of features that app developers will be trying to connect with smartwatch sensors. I mean, the volume of data produced and stored for subsequent analysis could easily double.
    1. Fitness promotions – now, you don’t have to be a professional athlete or sports star to monitor your own heart rate, the calories burned, and distance covered. The unsettling thing is, this type of information is going feral. And it’s marketing gold. So serious walkers can look forward to receiving mobile ads for all-terrain footwear. Flabby cycling enthusiasts could be targeted with the latest Lycra girdles. Also, gyms will be able to fiddle to their hearts’ content, with training plans based on ‘supersize-me’ client data.

    This is all ifs, buts, and maybes, of course. And perhaps this time – Shock! Horror! – the Apple Big Data bandwagon will pass us by.

    3 reasons smartwatches might not change Big Data after all

    1. Data privacy – do you really want your heart BPM broadcast indiscriminately to a world of strangers? Do you really want health companies and third parties to have total freedom to analyse and pirate your data for marketing purposes? What if you and I aren’t ready to give away our personal data?
    1. We already know what time it is – are expensive smartwatches really a ‘must-have’ for the regular Joe, Jo, or Jose? Most of us will carry on fishing for our phones when we need to know what the time is. And I can’t see traditionalists giving up their Swiss fashion statements easily. Time will tell.
    1. Built-in obsolescence – most sane people wait for the second or third iteration of a new piece of technology before committing hard cash, hoping all the bugs have been ironed out. Then we stick with it until, finally, we’re forced to upgrade. So, maybe apathy, resistance, or a lack of market penetration could kill off any real data explosion.

    So, what are we saying then?

    Over time, we’ve adjusted to the idea of underage footballers ‘earning’ a hundred times the average working wage, mayonnaise on chips, and Sunday shopping. So, no doubt, we’ll get used to wearing intrusive technology… eventually. Until then, smartwatches could easily remain the exclusive darlings of early adopters and trendies.

    But at the very least, adding the millions of Apple Watch sensors to the billions (soon to be trillions) driving the Internet of Things means creating more data, from which analysts can extract wide-ranging insights into consumer preferences.

    Personally? Give me the technical artistry of my Patek Phillipe, any day. And leave fruit in the fruit bowl.

    Where it can’t spy on me.

     

    This post first appeared on Forbes TeradataVoice on 27/04/2015.

    The post The Apple Watch Is Just A Big Data Wind-Up. Right? appeared first on International Blog.

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  • admin 9:47 am on September 26, 2015 Permalink
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    Increase Customer Conversion and Boost Revenue with On-Site SEO 


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  • admin 9:47 am on September 26, 2015 Permalink
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    Cyber Security for Public Health a cyber war game 


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  • admin 10:35 am on September 25, 2015 Permalink
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    Webinar: Increase Your Cybersecurity Effectiveness Using Big Data Analytics 

    Nearly half of US businesses reported a data breach in the past year.A logical response to these attacks is to add more cybersecurity applications or to increase the sensitivity of the applications currently in place. Unfortunately, this simply causes more alerts to be generated and/or an increase in false-positives, overwhelming your incident response team. Big data analytics can help you break out of this cycle. Our big data analytics approach to cybersecurity discovers patterns of activity upstream that signal impending attacks on your network so you can shut them down before they occur.
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  • admin 9:51 am on September 25, 2015 Permalink
    Tags: , , , , Debate, , Points   

    Key Points For Marketers In The Debate About Amazon’s Data-Driven Approach 

    a.com_logo_RGBAn article in The New York Times touched off a spirited debate about the work culture at Amazon, now the most valuable retailer in the country. One of the central issues at hand is that Amazon uses data not only to provide an exceptional customer experience, but also to manage its staff and improve productivity.

    To many of us, this news comes as no surprise. For years now, companies of all sizes have been increasingly turning to data analytics to improve employee engagement and performance.

    I also see it as indicative of the broad societal trends happening in today’s “data culture.” As a marketer, here are a few points to keep in mind while Amazon’s data-driven approach is in the spotlight:

    The data-driven shift is happening…now. There’s no denying that we’re moving toward more individualization – in the workplace, in the marketplace, in healthcare, etc. That means it’s time for you to progress beyond segmentation to true one-to-one individualization in a real-time context. Odds are, your competitors already have. In fact, in Teradata’s 2015 Global Data-Driven Marketing Survey, 90 percent of marketers said that making their marketing individualized is a priority. What’s more, the number of companies where data driven marketing is either embedded or strategic has more than doubled since we first started studying data-driven marketing trends two years ago. 78 percent of marketers now use data systematically; in 2013, only 36 percent did.

    Because data collection is increasingly ubiquitous, it’s shaping expectations. As data-driven approaches evolve, people are starting to expect more precise individualization, whether that’s in their performance reviews, fitness routines or shopping experiences. Your marketing campaigns need to meet those expectations. You need to understand your customers as individuals – each with his/her own preferences and behaviors –and then provide meaningful experiences based on that knowledge. As you do, be mindful that…

    The Creep Factor is real, and it can be mitigated. Critics of Amazon’s data-driven workplace say it’s too much like “Big Brother,” and from a consumer standpoint, there’s no doubt that when individualization goes too far, it stops being helpful and gets … well, “creepy.” To avoid crossing that line, you need to reach customers with what they want, when they want it and via the channel they prefer. If you’re looking for a single platform to help you create those kinds of customer relationships across all digital channels, you may want to consider Teradata Digital Marketing Center, a solution that brings together a wide spectrum of digital marketing channels and data in one platform through a SaaS-based solution for email, mobile, social, web marketing, segmentation, advertising and analytics.

    Your data-driven approach must align with corporate strategy. Another way to avoid being creepy (not to mention, unsuccessful): Don’t collect data for the sake of collecting data. Collect data so it leads to actionable insights. If you want to achieve desired business outcomes, you need a data strategy that permeates the enterprise, driven by a partnership between marketing, IT and other key business functions.

    Prescriptive analytics are on the horizon. As I mentioned in an earlier post, Google and Apple are rapidly developing technology to anticipate users’ needs and provide options for action. Prescriptive analytics are white hot right now… but that’s a topic for another day.

    What are you learning from the debate over Amazon’s data-driven approaches? Please share your insights below.

    The post Key Points For Marketers In The Debate About Amazon’s Data-Driven Approach appeared first on Teradata Applications.

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  • admin 9:48 am on September 25, 2015 Permalink
    Tags: , , , External, Fines, Internal,   

    Reducing Internal Costs and External Fines of Email Compliance 


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  • admin 10:36 am on September 24, 2015 Permalink
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    Presto, an Open Source SQL Engine for Big Data 

    Please join Presto founding engineers from Facebook and Presto contributors from Teradata. This talk will cover an overview of Presto, current use cases, technical talks of development efforts at both Facebook and Teradata, as well as future plans for Presto.
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  • admin 9:52 am on September 24, 2015 Permalink
    Tags: , , Finalists, , , , , ,   

    Teradata University Network Names 13 Finalists in International Big Data Talent Competitions 

    Next phase in helping major corporations fill their big data talent pipeline to be completed in October
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