IBM Brings Big Data Analytics to the Cloud, iPad
IBM (NYSE: IBM) has announced that its Hadoop-based data processing and analytics platform, InfoSphere BigInsights, is available on its SmartCloud Enterprise infrastructure, making big data analytics accessible for any user inside an organization.
The software was announced at the 2011 Business Analytics Forum, where IBM said the new Hadoop-based analytics software on the cloud analyzes traditional structured data found in databases and can also help employees tap into massive amounts of unstructured data from a variety of sources, including social networks, mobile devices and sensors.
According to IBM, the software sifts through all types of data behind the scenes and ranks it by quality, makes it secure, and ensures that business decisions are based on trusted data.
The new offerings span a wide variety of big data and business analytics technologies across multiple platforms, from mobile devices to the data center to IBM’s SmartCloud. Now employees from any department inside an organization can explore unstructured data such as Twitter feeds, Facebook posts, weather data, log files, genomic data and video, and make sense of it on the fly as part of their everyday work experience, said IBM.
For users, IBM has a free software download at Apple’s iTunes Store that the company claims will put mobile analytics into the hands of iPad users. IBM Cognos Mobile on the iPad is designed to help employees in key industries such as financial services, healthcare, government, communications, retail, travel and transportation use and benefit from analytics on the go.
For IT professionals and students, IBM’s BigDataUniversity.com will help those looking to build Hadoop skills. The new web site is a starting point for users to learn the basics of Hadoop, stream computing, open source software development, and database management techniques to prepare for careers as Data Scientists.
New Geographic Mapping for Predictive Analytics
New predictive analytics software with a mapping feature that can be used across industries for marketing campaigns, retail store allocation, crime prevention and academic assessment was also announced by IBM at the 2011 Business Analytics Forum.
SPSS Statistics 20.0 software includes a new mapping feature that gives users the ability to add a geographic dimension to analysis and reporting, and allows users to target, forecast and plan by geographical areas. This mapping feature can be used across industries to analyze data and create statistics for marketing campaign effectiveness, store allocation decisions in retail, detect crime hot spots, and for student test score assessments.
“The software comes with views of the United States, countries, continents and prebuilt map templates where users can quickly populate them with data including geospatial information from ESRI files,” said IBM.
Predictive Analytics for Healthcare
IBM also announced a solution for the healthcare industry that uses content analytics similar to what is found in IBM’s Watson technology.
Earlier this year, IBM said Watson would move on from Jeopardy! fame to healthcare. The result is the newly announced IBM Content and Predictive Analytics for Healthcare software that transforms raw information into healthcare insight quickly by revealing trends, patterns, deviations and predicting the probability of outcomes, allowing organizations to derive insight in minutes versus weeks or months.
According to IBM, its new predictive analytics software helps doctors and healthcare professionals to go far beyond traditional search and analysis of unstructured data. They can advance diagnosis and treatment by accurately extracting medical facts and understanding relationships buried in large volumes of clinical and operational data.
“IBM Content and Predictive Analytics for Healthcare uses the same type of natural language processing as IBM Watson, enabling us to leverage our unstructured information in new ways not possible before,” stated Charles Barnett, CEO of Seton Healthcare Family. “With this solution, we can access an integrated view of relevant clinical and operational information to drive more informed decision making. For example, by predicting readmission candidates, we can reduce costly and preventable readmissions, decrease mortality rates, and ultimately improve the quality of life for our patients.”
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