Here's the eighth video from our LUG conference.
Richard Tomlinson of Oracle gives us a demo of their Endeca Information Discovery (EID) engine, which is a mix of ecommerce, customer experience management, and business intelligence. Not something your everyday end user would be getting their hands on, right?
Richard joked that if you've ever run a search on an eStore such as Nike or Home Depot, or used the guided navigation bar on the left in those eStores, then you've used Endeca. Essentially, the engine was indexing whatever product catalogue and raw text came up, then summarized all the facets associated with that text
After that catchy intro, Richard uses the second half of his presentation to give us a demo of how they used the EID engine to help the Chicago police monitor social traffic around the Nato summit, by running a realtime social application powered by Salience that the police could watch all weekend. The engine is interesting in that Endeca developed it specifically to be able to address any type of data, be it structured, semi-structured, or completely unstructured.
Richard goes on to explain that they continued the job by scraping data from the National Counter Terrorism website. They dropped the data in Endeca, processed it with Salience, and used the results to expose the relationships between the scraped data and current mentions of them in social media. In this way, many relationships are exposed between two completely different datasets.
Richard Tomlinson has over 18 years experience in working with enterprise business intelligence, analytics, data warehousing and search technology at many leading software companies. He recently joined the Oracle product organization via the acquisition of Endeca Technologies, where his current job is to help drive the integration of the Endeca Information Discovery platform within existing Oracle products and applications. This role involves looking at new ways to fuse together unstructured and semi-structured information from documents, blogs, forums and social media with more traditional information from the data warehouse or other any other ERP, CRM, SCM, PLM, etc applications, to drive new insights and business value for the enterprise.
Recently, Richard has worked on projects that leverage Lexalytics capabilities to not only mine unstructured text for sentiment, themes and entities but have also allowed the same unstructured text to be mapped back to enterprise taxonomies including customer, product and service hierarchies or internal organization structures to uncover new linkages and pathways through data previously never considered that help explain drivers of business performance.