Predictive Analytics World London (30th November - 1st December, Business Design Centre) begins next Wednesday. Now is the final opportunity to make savings of £100 with pre-event prices, learn from industry experts and network with up to 2,000 key decision makers.
Final Opportunity to Attend Sessions Such As:
Multiple Case Studies: U.S. DoD, U.S. DHS, SSA.
Text Mining: Lessons Learned
Text Mining is the "Wild West" of data mining and predictive
analytics - the potential for gain is huge, the capability claims are
often tall tales, and the "land rush" for leadership is very
much a race. Discover from industry expert Dr John Elder the lessons
learned from real life case studies at US Government departments.
See also Dr Elder's full day workshop
Case Study: The Royal Bank of
Scotland
Value From The Long Tail
Arguing that extracting income from a large volume portfolio has become even more difficult in the past few years, Gaurav will show how predictive analytics has become key to identifying value in a banking portfolio. Use real examples from the Royal Bank of Scotland, he will demonstrate the growing importance of analytics in financial services.
Case Study: GlaxoSmithKline
Predictive Analytic Patient Recruitment and
Drug Supply Modelling in Clinical Trials
Patient recruitment and drug supply stage is a well-recognised bottleneck for the design and monitoring of clinical trials. Vladimir Anisimov of GlaxoSmithKline introduces software developed for risk based drug supply modelling, which have resulted in significant cost savings and benefits in R&D.
Case Study: BBC
Data Mining for Social Moderation
Mark Tabladillo and Fransisco Gonzalez of SolidQ demonstrate the challenges the BBC faced in providing social moderation of millions of posts and comments made on their public website. The session covers integration within a leading database platform, final model results evaluation and cost efficiencies and will demonstrate why more organisations will need to use enterprise solutions to handle high-volume social networking.