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Big Data Done Right by Successful Organizations

Big Data Done Right by Successful Organizations

Euro IT Group can help you unlock the tones of information already flowing through your organization, analyze it, extract value and transform it into insight that drives growth and revenue. Furthermore, by going through one of our big data quick wins programs, you will be able to enjoy the benefits of big data extremely fast, test and validate big data technologies and make better strategic decisions for managing your overall company data; our quick win program enables you to enjoy quickly new insights and measurable results by putting at work your existing data streams and to test and validate Big Data Technologies that can complement your legacy BI / DWH infrastructure.

Euro IT Group

July 09, 2015
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  1. Amazon Amazon has obtained a patent to ship us goods

    before we have even made a decision to buy them, purely based on their predictive big data analytics • the first retailer that used extensively algorithms to provide recommendations to customers • Anticipatory Shipping – some retailers already use predictive analytics to ensure the right items are in stock, based on past buying patterns, social media analytics and weather predictions. Amazon is taking it to a personal level, predicting items each user might buy using item-to-item collaborative filtering on many data points (eg: what users have bought before, what they have in their virtual shopping card or wish list, the items they have rated and reviewed, as well as what other similar users have bought) • ‘One Click Buy’ feature • Predictive big data analytics
  2. Mastercard They sell data to retailers, banks and governments on

    spending patterns found in the payments it processes MasterCard handles payments for 2 billion cardholders and tens of millions of merchants. It uses that information to generate real-time data on consumer trends, available more quickly that regular government statistics. "Retailers are fantastic at using the data they have available about how people shop in their store, how their inventory turns over, but what they don't know is what happens outside their store," she said. "The data we've got is ubiquitous across the whole market. We can help retailers see what they need to do to capture more sales.“ Ann Cairns, Head of MasterCard's business outside North America in Reuters interview
  3. Walmart “Our ability to pull data together is unmatched” Walmart

    CEO Bill Simon • Walmart’s attempt to use data to predict customer behavior date back to at least 2004 • WalmartLabs (2011) • The Social Genome project - aims to increase the efficiency of advertising on social networks by guessing what products people are likely to want to buy, based on their conversations with friends. • Shoppycat service suggests gifts that people might like to buy for their friends, based on their interests and Likes, and they also experiment with crowd-sourcing new products with Get On The Shelf. • Polaris - their own search engine - uses sophisticated semantic analysis to work out what a customer wants based on their search terms. • Smart lightbulbs containing Apple’s iBeacon technology to prepare to monitor shoppers in their stores • Walmart made a move from the experiential 10 node Hadoop cluster to a 250 node Hadoop cluster. They combined 10 different websites into a single one. Their analysis now covers millions of products and 100’s of millions customers from different sources. The analytics systems at Walmart analyse close to 100 million keywords on daily basis to optimize the bidding of each keyword.
  4. eHarmony Dating Site Personalized matches and search results for millions

    of subscribers to improve the chances of relationship success
  5. Cerner Healthcare Company Detect potentially fatal infections Cerner has built

    an enterprise data hub to create a more comprehensive view of any patient, condition or trends for over 1 million patients. Among other things, it is helping determine the likelihood that a patient has the potentially fatal bloodstream infection with a much greater accuracy than what was previously possible.
  6. Nippon Paint Domain: One of the largest paint manufacturers in

    the world Nippon Paint uses SAP HANA to understand consumer behaviors, optimize its supply chain and improve its marketing campaigns. They can quickly transform massive data from iColor website into valuable market insight for business actions. They built an analytics platform to capture consumer behaviors (eg: preferences on colors, design styles and designers, by demographic segments and geographic regions). They can quickly identify popular designers and decoration companies, allowing sales and marketing team to proactively build connections with them and to promote Nippon paint products. They can identify, on regional level, popular 3rd party portals which lead web visits to Nippon’s iColor website enabling them to place advertisements and push banners at the right portal to achieve maximum exposure. The first hand information on color trends and customer requirements on product features helps the R & D team to develop quality products to response to the market unique demands.
  7. Caesars – Luxurious Hotels and Casinos “Big Data is even

    more important than a gaming license” Joshua Kanter, VP of Total Rewards Caesar collects massive amounts of data and uses it to cultivate customer loyalty and surprise guests with gifts after, for example, a bad day at the casino. Their data-driven reward program has more than 45 million members, which are tracked from the moment they book until the moment they leave the hotel or casino. Due to the data-drive strategy, Caesars has been able to trace 58 percent of all costs spent to the customers in the company in 2004 to 85 percent today. Caesar tries to determine each guest’s profile. Cameras record action in the casinos and the choices the gamblers make while playing and combines this data with booking data, travel arrangements, dining, gaming and enjoying other activities at the company’s properties. All this information is stored, analyzed and used to increase customer satisfaction.
  8. Big Data Applied in Retail/eCommerce • Anticipate demand based on

    customer’s online activity, their geographical location, period of the year, weather, etc • Recommendations, advertisements or real time offers based on advanced customer segmentation and shopping patterns • Smarter shopping experience and smarter merchandising • Predictive analytics that enable you to optimize pricing, inventory levels, check your competition pricing, improve your customer service, increase customer satisfaction and your margins
  9. Big Data Applied in Digital Publishing • Use social media

    behavior patterns as “production line” • Relevant content delivered to the appropriate customer segment at the right time • Personalized content delivered in real time • Measure the effectiveness of your digital strategies and determine the most effective methods to deliver content to your targets • Transform big data into actionable insights
  10. Big Data Applied in Telecom • Products and services tailored

    based on customer behavior • Network infrastructure optimization • ARPU and up sell maximization by offering the right products based on customer behavior, context and service availability • Reaction time improvements in case of incidents • Detailed insights and maps showing the distribution and dynamics of revenue and churn versus the network type, quality or coverage • Upsell 4G • Telecom product recommendation • Users Location Profiling • Network Quality vs. Revenue and Churn
  11. Big Data Applied in Healthcare • Real-time analysis based on

    web search and social media or messaging contexts • Improved efficiency by integrating health care data and using them in the most optimum way • Customer care improvement based on better collaboration, customer knowledge and prevention strategies
  12. Big Data Applied in Distribution • Detailed customer information such

    as shopping patterns based on web logs • Inventory improvement based on social media analysis • Loads integrity, transit times • Fuel consumption and route optimization
  13. Big Data Applied in Financial Services • Contextual strategies and

    predictive analytics based on social media or messaging contexts • Contextual targeting - the right customer, at the right time and through the right channel based on cross channel data • Fraud detection based on analysis of historical data • Operational efficiency by consolidating data from different systems and multiple sources • Real-time alerting and reporting
  14. Euro IT Group Big Data Quick Wins with Hadoop &

    Understanding Benefits of Implementing Big Data with Hadoop Immediate Business Results • Generate new insights • Enabling short term business benefits • Measurable results • Test Hadoop Technologies • Complement traditional BI / DWH infrastructure with innovative solutions. • Expertise and Know How Approaching big data in small steps
  15. Domain Specialists Big Data Professionals • Ensures results are matching

    expectations. • Peers with operator marketing team. • Integrates multiple data sources • Develops or customize real-time and batch processing big data jobs. • Complex statistical data analysis requested by the marketing specialist. Big Data Specialized Delivery Team Data Scientist Software Engineers Marketing Specialist
  16. Technologies We Master JAVA: Apache Tomcat, JBoss AS, Jetty, IBM

    WebShere, Oracle, Application Server, WebLogic, Windows Server IIS, Nginx, NetWeaver) PHP: CodeIgniter, CakePHP, Zend, Yii, Kohana, Wordpress, Joomla, Drupal, MODX, Magento, Prestashop, IPBoard, Smarty ASP.NET, Visual Basic, ASP.NET AJAX, ASP.NET MVC, Remoting, Reflection, ADO.NET, Entity Framework MICROSOFT: C++, C#, ASP.NET, ASP.NET MVC, Silverlight MOBILE: Android, IOS, Windows 8, iPhone SDK, Android SDK, JQuery Mobile, Flash Lite, J2ME, Symbian, XMPP, SMS, WAP BIG DATA: Hadoop, Hadoop Map reduce, Spark, Storm, Mahout, Apache Pig, Apache Hive, Elastic Search, Cassandra, Apache HBase CLOUD: Amazon web services, Amazon EC2, Windows Azure
  17. Technologies We Master OTHERS: • Web Services: Apache CXF, Axis,

    SOAP, WSDL, JAXB, JAX-WS • Web technologies: XHTML, HTML5, XML, XSL, XSL-FO,XSLT, CSS, XPath, XQuery, SAX, DOM, StAX, Xerces, Flash, Flex • Content Management Systems: Stellent • Messaging Middleware: ActiveMQ, IBM MQ Series, Fiorano, MQSonic, TIBCO rendezvous WEB: HTML5, XML, XHTML, XSLT, DHTML, CSS, XSLT, Javascript, jQuery, PHP BUSINESS INTELLIGENCE: Pentaho BI, crystal Reports, Microsoft BI Microsoft Visual Studio, Windows API, ActiveX, XCode, wxWidgets, STL, WinDDK, Qt Framework, Microsoft CRM AJAX & JAVASCRIPT: JQuery, YUI, ExtJS, JSON,MooTools, Prototype JS, Dojo, YUI, Scriptacoulous, ASP.NET Ajax control Toolkit, etc.