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HAMR Validated in Silicon Valley5.27.2014

After peer review, the Academy of Science and Engineering (ASE) has accepted a breakthrough technical paper by ET International (ETI). “Beyond MapReduce: The Next Generation of Big Data Analytics” will be presented by ETI's Steve Turner on May 30, 2014, 11:00 AM at Stanford University's Tressider Memorial Union. ETI will also have a booth in the exhibit hall.

ETI will be in good company at the conference, which runs from May 27-31. Other enterprises presenting include IBM, Cloudera, Cray, Fujitsu, Samsung, HP, Pivotal, PricewaterhouseCoopers, Motorola and Microsoft.

The acceptance of the paper and ETI’s presentation affirms that the industry and academic community are open to HAMR for augmentation of the MapReduce (MR) core in the Apache Hadoop 2.0 ecosystem for big data (Big Data 2.0). The presentation will address appropriate use cases for MR, and new use cases enabled by HAMR, such as real-time data cleansing. ETI’s product offers a radically simpler solution that is already in beta testing. It has broad applicability – beyond Big Data 2.0.

HAMR is an analytics engine built with patent-pending data "flowlets.” Data scientists and programmers are able to manipulate flowlets in a single intuitive interface on a continuous basis. The framework has fewer steps and significantly faster data processing than existing technologies – advantages gained by optimizing the flow of data across computer hardware. This is the most sophisticated form of parallel processing.

HAMR enables data professionals to access and run analytics in multiple modes: batch, streaming and near real-time. It does not require data to be stored in, or run through data warehouses (DW) or the Hadoop distributed file system (HDFS2), but can accommodate those systems. Sources of big data include sensors, log files, feeds, social media, texts, email and operational data. HAMR’s flexibility is ideal in solving real-world problems associated with the big data revolution. These include data cleansing, contract analytics, electronic medical records, data discovery in the life sciences and fraud detection in financial services.

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Media Contact:

Dr. Long Zheng

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