NewsBig Blue unveils IBM Watson Engagement Advisor as a customer-facing search and answer tool with a marketing wrinkle and mobile components

blogData science roles may bridge analysis and insight
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CommentaryDon’t get overwhelmed by the sight of your data. And don’t make the mistake of throwing it away before it appreciates in value

TrendsHiring assessment by IT career resources site icrunchdata puts nearly half of available big data jobs in analytics, dwarfing categories such as business intelligence and statisticians
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ColumnLike the innovators of the smartphone, the firm that is first to successfully market a preconfigured application that pulls from structured, semi-structured and unstructured data will transform how enterprises do business forever
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CommentaryIBM CEO Rometty gives all marketers 18 months to “sink or swim”, though it’s happening even faster in health care and insurance

FeatureFour steps for implementing an agile marketing analytics strategy that can help organizations analyze their data in order to achieve goals

BlogBest practices to find and nurture business intelligence resources
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CommentaryWhile there is no silver bullet to solve the perceived shortage of data scientists, by taking a skills- and team-based approach, organizations can start addressing some existing business challenges
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Interview10 Minutes with Andy Rusnak, BI and visualization expert at Ernst & Young, on enterprise reluctance with agile development, what to keep in mind when presenting data from advanced analytic sources, and determining “intentional” mobile needs

Information Management's DM RadioMinor differences in meaning can result in major problems, especially when money is on the line. That's one reason why semantics really matter. Big data is another. The biggest challenge with big data is its unwieldy nature, but with semantic technologies, its meaning and relevance can often be quickly determined. Data science also benefits from the intuitive powers of semantics. And then there's the $30 million reason: the acquisition of Summly by Yahoo!, vaulting another 17-year-old to the top of the industry. Register for this episode of DM Radio to hear host Eric Kavanagh interview Sean Dillon of Agilex, plus Eric Franzon of SemanticWeb, Geoffrey Malafsky of Phasic Systems and Fiona McNeill of SAS Institute.

BlogAs innovators in MIT Sloan report suggest, fixation on performance brings adoption, ROI

Customer service optimization (CSO) is a technology-enabled discipline that puts customer service professionals in position to deliver outstanding service. The goal is to correctly resolve each incident without subjecting customers to time-consuming and annoying delays such as waiting “on hold,” having to explain their problem more than once or feeling that they are participating in on-the-job training of customer service agents. At the heart of CSO is the ability to access the best, most relevant and up-to-date information available in the organization. Therefore a robust and powerful search capability is an essential component. Being able to quickly find relevant data on a topic, regardless of where it resides and what form it is in, is often the key to achieving the goal of resolving incidents in a single call or interaction. Learn more in this informative white paper.