Karmasphere Announces Full Fidelity Big Data Analytics; Turning Big Data into Business Value Faster

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Personalized Analytics Dashboard Visual Data Explorer and Analytics Hub added to Karmasphere Workspace for Big Data Analytics

Karmasphere™, the leader in Big Data Analytics, today announced extensive new capabilities for the Karmasphere Workspace for Big Data Analytics, all designed to empower analysts to transform vast amounts of data into business insights. With the advances, Karmasphere recognizes the importance of providing full fidelity analytics for Big Data Analytics and the ability to explore all data directly without pre-processing, replicating or copying data into proprietary formats. Full fidelity preserves the richness and value of Big Data, delivers maximum flexibility, adheres to Hadoop standards and does not require expensive additional hardware.

Added to Karmasphere are an all-new Personalized Analytics Dashboard designed to organize Big Data analytics projects for individuals and teams, a Visual Data Explorer to provide the choice of visual data exploration or traditional SQL-tool based exploration, and an Analytics Hub to securely store, discover and manage analytic assets for sharing and reuse.

“Tools in-place now are more than twenty years old, designed for smaller data sets and processes, and they often require extensive re-copying of all the data into their proprietary systems,” said Sudhir Kulkarni, CTO and vice president of engineering for Karmasphere. “Karmasphere is designed for the era of Big Data; it enables all the analysts across a company to work together and benefit from the ease-of-use and power of full fidelity Big Data Analytics, without labor intensive data replication or extensive retraining.”

Karmasphere 3.0 includes

---Personalize Analytics Dashboard – Unique to Karmasphere is a personalized analytics dashboard that organizes and guides analysts through projects, visualizations and team interactions. Projects can be completed on time and within budget.
---Visual Data Explorer – A visual way to speed data analysis, along with the full, language-based power of SQL data exploration, giving users a choice of data exploration approaches.
---Analytics Hub – A centralized place for browsing, searching and reusing analytic assets including queries, results sets, visualizations and algorithms. Any User Defined Function (UDF) compliant with the Hive .11 standard can be ingested and managed within Karmasphere.
---Dynamic Data Lenses for Self-Service Analytics—the ability to create as many lenses as needed with no sampling or data duplication, and ingest both structured and unstructured data without IT assistance.
---Use of Existing SAS, SPSS and R Analytic Models – transform PMML models to Hadoop standard UDF’s, to run them across all your Big Data to increase accuracy and speed time to data insights.
---Over 250 pre-packaged Hadoop standard algorithms (UDF’s) available to jumpstart exploratory and predictive analytics.

To learn more about Karmasphere and view a demo of the Karmasphere Workspace for Big Data Analytics please visit Booth #34 at Hadoop Summit, June 26-27 at the San Jose Convention Center, San Jose, CA.

About Karmasphere
Karmasphere powers full-fidelity analytics on Hadoop with the most streamlined, open and enterprise-ready approach to Big Data analytics on the market today. The Karmasphere Workspace for Big Data Analytics is uniquely designed to natively extract value from Big Data without the need for abstraction or replication, which significantly reduces total cost of ownership and complexity. To make Big Data readily available to both data and business analysts, Karmasphere provides both Hadoop-standard SQL and visual data exploration. Karmasphere makes it easier for customers, such as Autodesk, Chevron, Chillingo, Intel and Supervalu, to deeply understand their customers and optimize their products, services and customer experience.

Learn more at http://www.karmasphere.com

Note: Karmasphere is a trademark of Karmasphere, Inc. All other trademarks are the property of their respective owners.

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