A Big Data Solution using JSONiq

Aug 27, 2013

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Big Data and Data Mining are spiking in usage and popularity. However, tools to access, transform and process data are running behind. What if there was an option that offered: - A high-level query language - these are critical to process the big data world into actionable information- Built-in distributed data processing capabilities from a variety of sources- Built in optimization features such as sharding- A comprehensive zero-install IDE on the cloud 28msec will present a case study of tools based on JSONiq where our customer has been able to focus on just extracting value out of their data. They been able to turn 1TB of USPTO data into data that is easy to use by attorneys performing trademark searches. We will also present other applications that involve mining of corporate and healthcare data. Speaker Bio Dr. Matthias Brantner - CTO of 28msec Matthias is passionate about all kinds of query optimization problems. He contributed to the development of one of the first research XML databases and query processors for semi-structured data. While working in academia and industry, Matthias published a variety of papers on the general topic of query processing and optimization. With one of the topics, he won the German doIT Software-Award. He studied Information Systems at the University of Mannheim and acquired a PhD based on his research on "Rewriting Declarative Query Language".

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