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IBM Helps Organizations Tackle Industry Specific Big Data Challenges

Hadoop-based Software for Industry-Specific Analytics   IBM InfoSphere BigInsights analyzes traditional structured data found in databases along with unstructured data to enable faster decision making. New features include built-in accelerators that analyze data flowing from digital infrastructures to help businesses in retail, manufacturing, oil and gas, energy and utilities, healthcare, and travel and transportation monitor operational efficiency, security incident investigation, proactive maintenance and troubleshooting and outage prevention.

BigInsights software now includes built-in social media analytics accelerators help marketers develop applications for customer acquisition and retention, perform customer segmentation and campaign optimization, and streamline lead generation. Employees can also select disparate data sources and instantly create new applications without the need for Hadoop skills.

BigInsights now features a new InfoSphere Data Explorer feature that enables advanced data federation capabilities from IBM's Vivisimo acquisition.  The software automatically discovers and navigates available data wherever it resides to reveal themes, visualize relationships, identify the value of data and establish context of data usage.

Building on the strength of IBM's big data platform and seamless integration with Business Analytics software, analytic reporting on Hadoop data with IBM Cognos BI and IBM Cognos Consumer Insight is a turnkey data to dashboard solution for sentiment analysis of social data. This ensures more decision-makers can benefit from big data organization-wide.

Predictive Analytics for SMBs in the Cloud Until now, predictive analytics has been deployed primarily by larger enterprises that are able to invest up front in the necessary software, skills and infrastructure. Analytic Answers offers small and medium sized businesses predictive analytics as a service, providing them access to the latest analytics capabilities without having to bring these skills or build models in-house. 

Clients enter their data and questions, related to enterprise challenges such as fraud, customer loyalty, or predictive maintenance, and receive quick answers. For example, a small insurance company can easily enter their data to determine who are their most likely customers are to renew a particular policy.  The service analyzes the data and provides an answer enabling the company to quickly act by tailoring a new policy.

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