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November 7, 2013

HP Launches Cloud-Based Analytics As a Service

BANGALORE, India, Nov. 7 — HP announced new cloud-based analytics as a service built on HP’s HAVEn Big Data analytics platform, helping clients solve business problems and create new revenue opportunities. By leveraging HP HAVEn, clients can more effectively analyze and derive value from their information, such as increase sales with targeted client offerings, improve supply chain performance, detect fraud or discover security risks.

HP Enterprise Services deliver end-to-end Big Data and Analytics solutions to make information actionable for clients in key domains and industries. Solutions include: Customer Intelligence, Supply Chain and Operations, and Sensor Data Analytics in industries such as Communications Media and Entertainment, Consumer Goods, Retail, Travel and Transportation, and Public Sector.

HP HAVEn enables organizations to create next-generation applications and solutions that accelerate the monetization of big data. HP HAVEn combines proven technologies, including HP Autonomy IDOL, HP Vertica Analytics Platform, HP ArcSight Security Event Manager and HP ArcSight Logger, as well as key industry initiatives such as Hadoop.

As one of the first adopters of the HP HAVEn platform, HP Enterprise Services deployed HAVEn as part of its Big Data Discovery Experience as-a-service offering, which allows customers to test drive and determine the value of their new use cases and “big data” data sets prior to making large capital investments.

As part of the HP Big Data Discovery Experience, clients have been able to quickly introduce challenges, engage HP’s data scientists and rapidly develop solutions that can be deployed either on premise or in the cloud.

HP’s Big Data Discovery Experience as a Service powered by HP HAVEn leverages HP’s Enterprise Services Cloud environment to provide flexibility and scalability. This enables HP to offer unique analytics solutions that solve complex problems involving the combination of structured (database content) and unstructured (emails, social media, digital, machine) data.

It can also apply analytical methods such as classification and pattern recognition related to audio, text and images, as well as statistical analysis involving large and complex data sets.

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