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Enterprise Analytics on Demand
Abstract:
Learn how eBay is taking the self-service analytics environment to the next level with Multi Petabyte Decision Support on Demand.
Internal analysts are able to build virtual data marts in minutes through self service portals. Templatized virtual data marts—the next generation of self-service—jump start solutions for analytics. Hundreds of virtual data marts share a single copy of the enterprise data. Data marts provide virtualization of analytical workloads on a massive scale.
This talk gives an overview of eBay's next generation Analytics as a Service platform that spans traditional data warehousing, BI, visualization, and real-time analytics.
Oliver Ratzesberger is Senior Director of Architecture & Operations for eBay, Inc. In this position Oliver is responsible for Cloud Computing and Analytics as a Service Architecture and Operations for eBay on a worldwide basis. Oliver came to eBay more than 5 years ago with more than 10 years' experience in extreme large-scale massively parallel grid systems, analytics, and data warehouse infrastructures. He has led analytics implementations in the financial and telecommunications industries in the US and Europe. Prior to his data warehousing experience, he managed IT systems and software development groups. Oliver holds a BSEE degree in Electronics and Telecommunications from Austria.
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BibTeX
@inproceedings {267501,
author = {Oliver Ratzesberger},
title = {Enterprise Analytics on Demand},
booktitle = {8th USENIX Conference on File and Storage Technologies (FAST 10)},
year = {2010},
address = {San Jose, CA },
url = {https://www.usenix.org/conference/fast-10/enterprise-analytics-demand},
publisher = {USENIX Association},
month = feb
}
author = {Oliver Ratzesberger},
title = {Enterprise Analytics on Demand},
booktitle = {8th USENIX Conference on File and Storage Technologies (FAST 10)},
year = {2010},
address = {San Jose, CA },
url = {https://www.usenix.org/conference/fast-10/enterprise-analytics-demand},
publisher = {USENIX Association},
month = feb
}
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