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  • Cloud machine learning still an answer in search of a question

    Cloud machine learning is still a talking point in IT circles as vendors try to make it more palatable to mainstream enterprises. Continue Reading

  • Salesforce rallies in retail with purchase of Demandware e-commerce

    Now that Salesforce has purchased Demandware, it's positioned to compete with vendors like Oracle and even Amazon for market share. Continue Reading

  • Predictive marketing analytics illuminates best sales leads

    Being able to foretell the future would make a lot of people's jobs easier. Teachers would know which students are going to struggle on a test and could offer them extra attention, doctors could identify health problems before patients get sick and sales representatives would know which prospects to spend the most time courting. Luckily for the last group, predictive marketing analytics has emerged to help them anticipate and follow the right leads.

    This guide looks at how predictive marketing analytics can boost the efficiency of the sales funnel. In the first article, consultant Steve Robins introduces predictive analytics and explains how it should be used and the importance of having a strong model. Next, marketer Matt James gives real-world examples of analytics being used to create more customer-specific advertisements and hire more promising workers. Robins closes with an article on how predictive lead scoring can help sales and marketing teams work together better.

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  • Advanced analytics tools extract business value from big data

    Big data environments based on technologies such as Hadoop and Spark are being deployed more widely -- and the same goes for advanced analytics tools that can help organizations make effective use of the data flooding into those systems. In fact, predictive analytics software was the top choice for planned business intelligence and analytics investments by respondents to a TechTarget survey.

    And in many cases, deployments of advanced analytics software to support big data applications aren't a one-and-done thing. Macy's uses more than a half-dozen tools to meet different application needs as part of the retailer's big data analytics program. The technology roster includes statistical analysis, predictive modeling and machine learning tools that Macy's couldn't do without. "Because of the volume of data, there's just no humanly possible way to analyze it [manually]," said Seetha Chakrapany, the company's director of marketing analytics and customer relationship management systems.

    Macy's is just one of six organizations featured in this e-book chapter by Executive Editor Craig Stedman. Progressive Casualty Insurance Co. is another. The insurer's data and analytics business leader, Pawan Divakarla, said the capabilities provided by advanced analytics tools are "huge" in enabling Progressive to manage a program for awarding discounts on auto insurance policies to safe drivers based on analysis of operational data collected from their vehicles.

    But there are issues to contend with along the way, from the complexity of developing predictive models and machine learning algorithms to the challenge of sharing analytics results with business executives. Find out how Macy's, Progressive and others have overcome the hurdles and made advanced analytics against pools of big data work successfully.

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  • Launching big data initiatives? Be choosy about the data

    Thanks to open source technologies like Hadoop and lower data storage costs, more organizations are able to store multi-structured data sets from any number of internal and external sources. That's a good thing, because valuable insight could lurk in all that info. But how do organizations know what to keep and what to get rid of? It's a problem that the February issue of Business Information aims to solve.

    In the cover story, SearchBusinessAnalytics reporter Ed Burns talks to businesses that have learned just what to tease from their data. Take marketing analytics services provider RichRelevance, which runs an online recommendation engine for major retailers such as Target and Kohl's. The company has two petabytes of customer and product data in its systems, and the amount keeps growing. To sift through it for shopping suggestions, RichRelevance looks at just four factors: browsing history, demographic data, the products available on a retailer's website and special promotions currently being offered. That way, it keeps its head above the rising tide of data.

    And finding themselves surrounded by a sea of data, businesses are finding it's increasingly important for to know how to swim. Many turn to the waters of the data lake, hoping to cash in on the benefits the Hadoop-based data repository promises. But the data lake may not be as tranquil as it sounds, reporter Stephanie Neil writes. Data governance challenges abound, and changes in workplace culture will most likely be required to make it work.

    The issue also features a brand-new column. It's insight from a CIO for CIOs. Or would-be CIOs. The inaugural installation, by Celso Mello, of Canadian home heating and cooling company Reliance Home Comfort, dishes up advice for those wishing to climb the corporate ladder to the C-level.

    The issue also puts the spotlight on an IT manager at a Boston nonprofit who used the skills inherited from her political family to usher in a human capital management system upgrade. It also captures some of the wants and needs of BI professionals who attended TechTarget's 2014 BI Leadership Summit, last December and takes a look at the origins and prospects of open source data processing engine Apache Spark. The issue closes with a few words by Craig Stedman, executive editor of SearchDataManagement and SearchBusinessAnalytics, on the hard work needed to put in place an effective business intelligence process.

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  • Strategies for finding analytics skills, despite the shortage

    The shortage of skilled analytics professionals is well documented, but SAS conference attendees said businesses that know where to look can find, or develop, the skills they need. Continue Reading

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