StubHub's Data Scientists reap benefits of integrated approach….
We have released yet another great video customer video, this time with StubHub.
StubHub provides the world's largest fan-to-fan ticket marketplace. The company was formed in 2000 and now dominates the market by making sure fans have a truly open marketplace where they can buy or sell tickets without restrictions or limitations. For more information about SubHub and its services visit their website: http://www.stubhub.com
StubHub's is now getting real business benefit from moving their data analytics inside their data warehouse. This seems like an obvious way to build your data warehouse but many customers are still pulling data out of their data warehouse and shipping it to specialised processing engines so they can mine their data, run spatial analytics and/or built multi-dimensional cubes. The problem with this approach, as the team at StubHub points out, is that typically when you move the data to these specialised engines you have to work with a subset of the data that is sitting in your data warehouse. When you work with a subset of data you immediately start to impose compromises on your analytical workflows. If you can't work with all your data then you can't be sure that your analytical model is as good as it could be and that could mean losing customers or missing out on additional revenue.
The other problem comes from everyone using their own favourite tool to do their analysis: how do you share your discoveries, how do you develop a high level of corporate-wide analytical skills?
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StubHub asked Oracle to help them resolve these two key problems. Their data scientists have now adopted open source R as their standard tool for data mining projects. By adopting Oracle's R Enterprise solution they have been able was to push all their analytical processing that is linked to their data mining workflows back inside their Oracle Data Warehouse. Oracle Advanced Analytics is optimised to provide real-time analytics that delivers insight into key business subjects such as product recommendations, and fraud alerting. Most importantly because the data mining workflows run inside the Oracle Database the data scientists have access to all the data inside their data warehouse and no longer have to rely on extracting small subsets of data, the data remains completely secure and they can benefit from the built-in operational scalability of the Oracle Database.
For more information about Oracle's R Enterprise solution use the following link: http://www.oracle.com/us/products/database/options/advanced-analytics/overview/index.html.