Question - In the past data was collected by manual methods where you can rigorously ensure validity of your dataset. What are the start of art techniques for automating data validity in a streaming big data fashion/challenges going forward? - Mike P.
Automated listening is the huge thing I see; Then semantic analysis will give contextual relevance to the data in question; data in context is very important
I agree. It does come down to harnessing the intelligence found in the RIGHT information. Companies need solutions to help them mine through the copious amounts of data to discover what the RIGHT information looks like.
@ambarmstrong Right! airlines are in such a highly competitive industry that to offset low margins can use #ibmwatson to help them in predictive analytics
A2 it's easier in some industries than others to gain access to #analytics and #socbiz. Financial/banking institutions have more compliance/security issues to be mindful of than retail, for example.
yes that's why a one-size-fits-all product won't work, and IBM Services could excel... companies like Amazon, Pinterest and Square are examples of success
@MattPCleveland Understand. Yet when I buy a book in person at Barnes & Nobel (for example) using my B&N card I'd appreciate them acknowledging that I'm a frequent shopper and I'd like them to highlight relevant new books in the store to me.