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    big data analysis

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    WINTER 2011 V O L . 5 2 N O. 2 Steve LaValle‚ Eric Lesser‚ Rebecca Shockley‚ Michael S. Hopkins and Nina Kruschwitz Big Data‚ Analytics and the Path From Insights to Value REPRINT NUMBER 52205 THE NEW INTELLIGENT ENTERPRISE Some of the best-performing retailers are using analytics not just for finance and operational activities‚ but to boost competitive advantage on everything from displays‚ to marketing‚ customer service and customer experience management. Big Data‚

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    Retail Loss Prevention

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    with Analytics February 2009 DRAFT Abstract T he retail industry is in the middle of an unprecedented economic crisis. All retailers are trying to figure out how to cut costs‚ retain customers‚ conserve cash and more importantly stay in business. Recently‚ the National Retail Federation (NRF) polled readers of its SmartBrief asking them what was on top of their mind. Loss Prevention (LP) came in second only to the overall economy! It is no surprise given that every dollar saved from retail

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    Abstract: The existing business paradigm of data analytics is set for a transformation. Today‚ companies are experimenting to replicate the “Outsourced data analytics” model to “Crowdsourced data analytics”. Companies like Kaggle‚ Crowdanalytix and others are hitting the headlines of top analytics blogs across the globe. The reason is that the new business model promises a drastic decrease in the cost of analytics for companies long with the flexibility to get the problem solved anytime with much

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    Data Warehousing and Olap

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    analysis; server extensions for efficient query processing; and tools for metadata management and for managing the warehouse. 1. Introduction In the 1990s‚ as businesses grew more complex‚ corporation spread globally‚ and competition became fiercer‚ business executives became desperate for information to stay competitive and improve the bottom line. Data warehousing technologies have been successfully deployed in many industries: manufacturing (for order shipment and customer support)‚ retail (for user

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    Big Data

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    M.‚ Roxburgh‚ C.‚ and Manyika‚ J.‚ 2011. Big Data : The next frontier for innovation‚ competitio‚ and productivity. McKinsey Global Institute Research‚ pp.11-146. Brynjolfsson‚ E. & McAfee‚ A.‚ 2012. Big Data: The Management Revolution. Harvard Business Review‚ 90 (10)‚ pp. 60-66‚68‚128. Corn‚ A. and Nguyen‚ H. and Parameswaran‚ A.‚ 2012. Big Data. The AMC Magazine for Student‚ 19 (1)‚ pp. 7-8. Davey‚ N.‚ 2012. What is Big Data and how can it be applied for marketing? [online]. Available from: http://www

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    for organizations‚ including small businesses‚ to analyze it internally. The analysis examines an organization’s assets‚ processes and past levels of achievement. While SWOT analysis provides some benefits to an organization‚ using it in your small business can put you at a disadvantage unless you understand its limits and risks. Other Planning Methods Perhaps one of the biggest disadvantages of using a SWOT analysis comes when the organization makes the decision‚ whether conscious or not‚ to only rely

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    which means they are back to square one and must request additional information. Often executives receive multiple‚ conflicting information or information that is based on incomplete assumptions about the types of analysis required. Problem The business problem to be solved is how to build the reporting process by eliminating manually intensive reporting‚ providing accurate information in a timely manner and building the foundation (Robust Data Warehouse) for a fully integrated global reporting

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    Marketing Big Data

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    Introduction Big Data is indeed a better idea. Every day‚ we create 2.5 quintillion bytes of data–so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: posts to social media sites‚ digital pictures and videos posted online‚ transaction records of online purchases‚ and from cell phone GPS signals to name a few. This data is big data. “Much like the scientific principle that we can’t observe a system without changing it‚ big

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    individuals and businesses to monitor and interact through multiple social networks from a web-based dashboard. Features We can organize our dashboard by using “tab” and “stream.” Like folders in our computer‚ tabs help separate and categorize our business and personal social networks and apps into unique spaces for easier viewing. Every stream inside your tab is self-contained. So we can monitor the Tweets‚ Facebook photos‚ and YouTube searches related to our Tab title. HootSuite Mobile HootSuite

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    Analytics

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    WHITE PAPER Predictive analytics The rise and value of predictive analytics in enterprise decision making “Give me a long enough lever and a place to stand‚ and I can move the Earth.” Archimedes‚ 250 B.C. In the past few years‚ predictive analytics has gone from an exotic technique practiced in just a few niches‚ to a competitive weapon with a rapidly expanding range of uses. The increasing adoption of predictive analytics is fueled by converging trends: the Big Data phenomenon‚ ever-improving

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