Qubit Adds Machine Learning to Big Data Analytics Service

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    How to Evaluate Predictive Analytics for Your Business

    One of the places that Big Data analytics and machine learning is obviously going to have a massive impact is in improving the customer experience. But given both the amount of data involved and the complexity of the programming models involved, it’s becoming more apparent that most organizations are going to wind up consuming these technologies as a service.

    Qubit this week announced that it is adding a machine learning engine to a digital experience management (DXM) platform aimed primarily at marketers. Bud Goswami, head of data science at Qubit, says the Qubit ML engine automatically identifies and prioritizes customer groups by their largest revenue opportunities using a combination of predictive analytics machine learning algorithms to enable marketers to create personalized experiences for different type of customers.

    Goswami says it’s simply going to be more economical for organizations to consume Big Data as a service. In fact, Goswami notes that most organizations are not especially interested in the raw data. It’s the analytics derived from that data that creates the actionable intelligence they crave, says Goswami.

    The need to infuse analytics with machine learning algorithms, adds Goswami, puts the core technologies that organizations would need to invest in to replicate the same capability Qubit provides on their own out of the economic reach of most organizations.

    “DXM is designed to isolate the marketer from all that technical complexity,” says Goswami.

    Naturally, most IT organizations are naturally pre-disposed to own as much of the IT environment as possible. But as IT gets more advanced many of them will need to ask themselves how much longer it makes sense to invest in IT infrastructure versus simply renting the outcomes the business was originally interested in having access to in the first place.

    Mike Vizard
    Mike Vizard
    Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

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