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  • admin 10:33 am on September 30, 2015 Permalink
    Tags: , , , , , , Tighter,   

    Webinar: First in Class: Optimizing the Data Lake for Tighter Integration 

    Learn from veteran Analyst Dr. Robin Bloor as he discusses the relevance of data lakes in today’s information landscape. He’ll be briefed by Mark Cusack of Teradata, who will explain how his company’s archiving solution has developed into a storage point for raw data. He’ll show how the proven compression, scalability and governance of Teradata RainStor combined with Hadoop can enable an optimized data lake that serves as both reservoir for historical data and as a “system of record” for the enterprise.
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  • admin 9:51 am on September 30, 2015 Permalink
    Tags: , DevOps, Extend, , ,   

    Teradata First to Extend DevOps to the Data Warehouse 

    Launch of open source Teradata Module for Python enables programmers to easily create a new generation of applications that exploit the data warehouse
    Teradata News Releases

  • admin 9:51 am on September 30, 2015 Permalink
    Tags: , smallscreen,   

    It’s a small-screen world 

    mobileusersSQThis post originally appeared on The Economist Group’s Lean back blog.

    The average person’s attention span is now even shorter than a goldfish’s, and mobile is pervasive, with activity on smartphones and tablets accounting for 60 percent of digital media time spent in the U.S. No wonder so many marketers are intent on creating brand messaging that’s easy to notice, easy to read and easy to digest. But if that’s your principal focus, are you also creating sales and marketing content that’s easy to forget?

    Today’s marketing campaigns must appeal to distracted, small screen users on the move, and we all know visuals are preferred over text. That means if you want to get your message across, the writing itself must adapt.

    As content expert Neil Patel explains: “For mobile content, concise writing is essential. In this case, the necessity has more to do with the screen size than the user’s attention span. Your goal is to present the user with as much on-screen information as possible without requiring the user to swipe or tap. The more cogently you can express an idea, the better.”

    Even so, images and writing alone aren’t enough. You also need data-driven marketing. I’ve seen too many companies invest resources to ensure downloads of snazzy new apps, only to be disappointed. It’s as though achieving metrics around downloads overshadowed the app’s real purpose: individual customer engagement.

    Your objective isn’t to market an app. Your objective is to connect your brand with individual customers. Research shows that despite the numerous apps downloaded, few are used after the first few times.

    Wouldn’t it make more sense to devote your efforts to increasing engagement among existing users? To do that, you need to:

    • Return to basics—your brand: A strong brand resides within the hearts and minds of customers. Make sure your app delivers your message clearly.
    • Put attention where it belongs—on the customer: Design your app around the needs, wants and preferences of your customers. Offer value.
    • Extend the customer relationship by developing individualized interactions that draw on customer data: Use real-time data-driven marketing to build ongoing relationships and enhance customer loyalty.
    • Use the new interactions to glean even more insights: Analytics enable you to architect better experiences, increase value to customers and ultimately, generate greater revenue.

    As always, the success of your enterprise marketing strategy depends on solutions that boost real-world business transactions, whether those actions happen via an app or some other channel.

    The post It’s a small-screen world appeared first on Teradata Applications.

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  • admin 9:47 am on September 30, 2015 Permalink
    Tags: , , Germany, , ,   

    Teradata State of Germany Shopping Apps 2015 

    Teradata White Papers

  • admin 9:54 am on September 29, 2015 Permalink
    Tags: , , , , , Trailer,   

    Trailer Four Truths of Real Time Customer Engagement 

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  • admin 9:52 am on September 29, 2015 Permalink
    Tags: , , , , ,   

    Teradata Accelerates Roadmap for Open Source Presto 

    Teradata responds to community’s request for enterprise-class ODBC/JDBC Drivers for Presto; opening business intelligence and analytic applications for the open source query engine
    Teradata News Releases

  • admin 9:52 am on September 29, 2015 Permalink
    Tags: , , EnterpriseReady,   

    Enterprise-ready Hadoop, Now Available as an Appliance 

    By: Clarke Patterson, senior director of product marketing, Cloudera

    Early this summer, Teradata and Cloudera jointly announced the Teradata Appliance for Hadoop with Cloudera, an engineered, ready-to-run appliance that comes with enterprise-ready Cloudera Enterprise, in addition to our existing software integrations.

    Today, at Strata + Hadoop World at New York, we are excited to announce the ability for customers to now order the Teradata Appliance for Hadoop with Cloudera.

    Over the last couple years, we have certainly seen the maturation of Hadoop and the shift from using Hadoop as a proof-of concept technology to an enterprise-ready platform. However, the time, skillsets, and resources needed is hard to come by, and not every organization has the ability to hire the best talents in the market to plan, deploy, and manage Hadoop clusters, let alone support and maintain the platform post-production.

    The Teradata Appliance for Hadoop with Cloudera is built to satisfy the need to stand up a Hadoop cluster quickly and cost-effectively. Having an appliance allows organizations to simplify and accelerate the cluster deployment, enabling customers to focus their IT resources on fine-tuning the infrastructure to deliver business value, rather than investing valuable resources in the details of deployment, management, and support of the platform.

    In addition to the benefits of an appliance form-factor, the Teradata Appliance for Hadoop with Cloudera also delivers all the benefits of enterprise-ready Hadoop with Cloudera Enterprise:

    • Enterprise security and governance for all mission-critical workloads – With Apache Sentry and Cloudera Navigator, Cloudera Enterprise provides multiple layers of security and governance that are built to maintain the business agility and flexibility that Hadoop provides, while providing the security necessary to meet stringent security regulations and requirements. Being compliance-ready at the core, Cloudera Enterprise is the only distribution that is fully PCI-certified.
    • Industry-Leading Management and SupportCloudera Manager features a best-in-class holistic interface that provides end-to-end system management and zero-downtime rolling upgrades. Combining the power of Cloudera Manager with Teradata Viewpoint and Teradata Vital Infrastructure, Teradata Appliance for Hadoop with Cloudera provides intuitive tools for centralized management with powerful capabilities, even as the system scales.
    • Built on open standards – Cloudera is the leading open source Hadoop contributor, having added more major, enterprise-ready features to the Hadoop ecosystem, not just to the core. Over the years, Cloudera has been working with large ecosystem of partner and development community members to promote open standards for data access and governance through Cloudera Accelerator Program and One Platform Initiatives. With the Apache-licensed open source model, Cloudera ensures that data and applications remain the customer’s, and an open platform to connect with all of their existing investments in technology and skills.

    With all the hustle and bustle of Strata + Hadoop World this week, don’t forget to stop by the Cloudera booth and the Teradata booth to talk to us about the Teradata Appliance for Hadoop with Cloudera!

    Clarke Patterson, product marketing, ClouderaClarke Patterson is the senior director of product marketing at Cloudera, responsible for  Cloudera’s Platform for Big Data. Clarke joined Cloudera after spending almost three years in a similar role at Informatica. Prior to Informatica he held product management positions at IBM, Informix and Red Brick Systems.  Clarke brings over 17 years of leadership experience to Cloudera having lead teams in product marketing, product management and engineering. He holds a Bachelor of Science degree from the University of Calgary and an MBA from Duke University’s Fuqua School of Business.

    The post Enterprise-ready Hadoop, Now Available as an Appliance appeared first on Data Points.

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  • admin 9:52 am on September 29, 2015 Permalink
    Tags: , Fifteen, , , Safeguarding, ,   

    The Future of Cyber Security Fifteen Trends Safeguarding Government 

    Teradata White Papers

  • admin 9:53 am on September 28, 2015 Permalink
    Tags: , , ,   

    Forget End State Architecture – Aim for Endless State 

    Often working and discussing amongst peers and customers I hear the term “end state architecture”. It sounds like some magical nirvana where we all work hard to deliver and configure a solution that will meet all of the expectations (and maybe solve world hunger at the same time) at a point in time in the future. The sales division of vendors is partly responsible for this approach because the story usually starts off by defining the current problem as this mass of integration points/issues as depicted below:

    To an end state where life seems so much easier and simple.

    If only it was so easy……

    So in architecture should we aim for an “end state”? Shouldn’t we be aiming for an architecture that will support the business objectives at that particular point in time in the future? Whilst at the same time ensuring our architecture is flexible and adaptable if those business priorities change during the course of the project. Thus the endless state architecture concept.

    The last point above is important because too often we see an end state set in stone and all of a sudden the business priorities change and the cost to shift away from the end state is prohibitive and thus IT pushes on to deliver a solution that all of a sudden doesn’t support the business and the project becomes an expensive white elephant.

    The speed and rapidly changing nature of the analytics industry dictates that we shouldn’t have an end-state architecture but rather an architecture that evolves and adapts as the business changes. In essence there is never an end-state. A bit like a chameleon having to change it’s colour based on the environment it is in.

    Whether we like it or not, that’s the present day operating environment that we have to design architectures in. If you go down to a lower level and apply a traditional architecture approach to Hadoop and Big Data architectures, you’ll forever be chasing your own tail. Hadoop architectures, products and functionality are released at such a rapid rate that for me it is basically a full time job keeping on top of it all. So what’s the point of having an end state architecture when we’ll never reach it? It’s a major contributing factor as to why 68% of IT projects fail.

    Michael Nygard delivered a great speech on the concept of an endless- state architecture. The concept outlined here is that we should create architecture that is specifically optimized for change, with principles about where to place certain decisions and how to adapt over time. Optimized for change is important and as much as possible an architecture should be modular in it’s design. Each component should be best of breed, integrate together yet be swapped in or out over time to adjust to the changing business landscape. Another term applied to this concept is the sentinent enterprise.

    Lastly an evolving architecture also relies on the human element to succeed. The continuity of a cohesive team to deliver the architecture, the tenure of a CIO to ensure it is supported at the executive level and of course the developers and project managers at the coal-face to deliver the functionality to meet the requirements.

    Key tenants of an endless state architecture:

    • Use of open source technologies
    • Enterprise integration standards such as SOAP and Rest Services
    • Commodity hardware that is swappable
    • Skillsets within the team that are relevant and adaptable

    An eye on the changing priorities of the business.

    Ben Davis is a Senior Architect for Teradata Australia based in Canberra. With 18 years of experience in consulting, sales and technical data management roles, he has worked with some of the largest Australian organisations in developing comprehensive data management strategies. He holds a Degree in Law, A post graduate Masters in Business and Technology and is currently finishing his PhD in Information Technology with a thesis in executing large scale algorithms within cloud environments.

    The post Forget End State Architecture – Aim for Endless State appeared first on International Blog.

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  • admin 9:51 am on September 27, 2015 Permalink
    Tags: , , Needle,   

    Data Science – What if the Needle is Made of Hay? 

    “Finding a needle in a haystack” is perhaps the most overused quote of the data science trade, with most material promising to sift/burn/search the haystack faster than before to find the vast stack of needles it hides underneath. In reality, however, there is not always a needle and even when there is, we may not know what it looks like.

    Within the context of data science, the haystack is the mass of available data while the needle is the valuable insight or answer. Metaphor-extending shenanigans aside, this idiom is misleading: it implies we know how the needle looks like, and also that the insight is distinctly different from the data; in fact insights come from the data.

    Too often, a failure to find the needle is attributed to the staff performing the analysis or the technology used. In a previous post about the scientific method , I argued that there was no such thing as failure: a hypothesis can be rejected or not, but both are valid answers in the eyes of science (if not in the eyes of the business). If the question asked is “what action can I take to reduce churn by 50%?” under the constraint that significantly reducing prices is not an option, the answer may well be nothing*. There is no needle, and yet the science hasn’t failed the business**.

    In physical sciences, there often is a needle. What’s more, scientists have a pretty good idea how the needle looks like, as theory and repeated scientific experiments give an ever increasing precise understanding of the world. In behavioural sciences, however, confounding factors are multiple, and customer behaviour is not (yet?) fully understood. As a result, we do not know how the needle looks like, or even if there is one. The question “find a demographic split that leads to a customer segment with 50% probability of buying item X” may not exist, may be too small to be meaningful, or may not be actionable. Following the scientific method, however leads to scientifically valid answers that should be used to acquire more/different data, design new experiments or refine the original question.

    Does failing to find a pre-specified needle show a fundamental limit to what data science can achieve? In short: no. Discovery is an iterative process: successive predictions, testing, and design of experiments separate the wheat from the chaff. Hypothesis -> Testing -> New Hypothesis -> New Test -> etc… Sorting and filtering the stack of data strand by strand is ultimately what data science is about.

    The needle is not always there, and is often not made of gold. In fact, in the beginning there is no needle, but successive tests, experiments, and regular engagement between scientists and business experts allows everyone to understand the haystack better, and, strand by strand, to construct a needle made of hay.

    * In reality the answer may be that doing X and Z will reduce it by 35%. How acceptable that answer is will vary.

    ** When the business provides both the question and the answer form the onset it may, however, fail the science.

    Clément Fredembach is a data scientist with Teradata Australia and New Zealand Advance Analytics group. With a background in Colour Science, Computational Photography and Computer Vision, Clement has designed and built perceptual statistical experiments and models for the past 10 years.

    The post Data Science – What if the Needle is Made of Hay? appeared first on International Blog.

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