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"Can SODA (Search over DAta Warehouse) Quench the Thirst of Business Analysts?"

One of the main assets of a bank is data. The ability to search through large piles thereof was particularly challenged in September 2008 when the crash of the US investment bank Lehman Brothers caused a worldwide crisis. In order to reduce the damage, banks around the globe had to act quickly and identify which customers had investment products related to Lehman Brothers.  This required close collaboration between IT and business departments to dig into terabyte to petabyte-scale data warehouses to find the respective customers and investment products.
A short coming of most modern enterprise data warehouses is that they are typically very complex and only highly specialized IT experts manage to sieve through the data flood. In this talk we present a prototype system called SODA (Search over DAta Warehouse) that enables non-tech savvy business analysts to explore the data without in-depth IT knowledge in an intuitive and easy way. Our system has been built as a joint research effort between Credit Suisse and ETH Zurich and combines database technology and graph theory with semantic web features. We elaborate on the design and implementation of SODA and show experimental results with both synthetic and real data.  The results demonstrate that our approach works well for analyzing real data of a large financial institution with a Google-like keyword search approach.

Dr. Kurt Stockinger, Credit Suisse

Dr. Kurt Stockinger, Credit Suisse

Dr. Kurt Stockinger is a data warehouse (DWH) and business intelligence (BI) architect at Credit Suisse, Zurich since fall 2007. He works on designing and prototyping DWH algorithms for a terabyte-scale enterprise warehouse,  data security, and DWH/BI
applications. Since early 2009 Kurt has been working on several joint research projects between Credit Suisse and ETH Zurich as part of the Enterprise Computing Center.
Prior to joining Credit Suisse, Kurt worked for four years at Berkeley Lab, University of California, performing research on multi-dimensional indexing and query methods for large-scale scientific data as well as high-performance visual analytics (query-driven visualization on modern supercomputers). From 2000 to 2003 Kurt was heading the Replica Optimization Team of the EU Data Grid Project at CERN. In 2008 he received an "R&D 100 Technology Award" together with three colleagues from Berkeley Lab for his research on FastBit – a multi-dimensional bitmap index engine that was applied for query acceleration in the areas of high-energy physics, astrophysics, and combustion simulation as well as computer network security. Kurt holds a Ph.D. in computer science from CERN / University of Vienna.

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