Why Expanding Signal Hunting Skills Is Crucial To Big Data Success
One of the key observations about the difference between big data sources and those traditionally used by enterprise applications is the strength of the signal. As Anant Jhingran, VP Products of Apigee, pointed out in an interview a while back, traditional enterprise applications use data that has super strong signals, while big data usually has a low signal to noise ratio.
This matters mightily to anyone who has ambition to find value in big data. The key enabler is to create as many people as possible who can engage with one or more big data sets along with relevant contextual data and find the useful nuggets or “signals”. If you don’t have a strategy for growing the number of signal hunters in your organization, big data will remain an artisanal activity, and the real opportunity to create value will be lost.
But how? The best answer I’ve see so far comes from Trifacta, which has methodically attacked this problem and focused intense energy on the user experience challenges, not just on the data science.