The big data steam roller continues to move forward, but if you take a brief step back, how would you define “big data?” UC Berkeley’s new Master of Information and Data Science program decided to settle the question once and for all, and asked 40+ thought leaders in publishing, fashion, food, automobiles, medicine, marketing and every industry in between how exactly they would define the phrase “Big Data.” Their answers might surprise you.
The results of the project feature people like Hilary Mason, Drew Conway, Hal Varian, Gregory Piatetsky, and many others. The group knew the term was vague so they figured the best way to get a handle on it was to ask those who are immersed in the field. You can check out the full list HERE.
Here are some highlights:
While the use of the term is quite nebulous and is often co-opted for other purposes, I’ve understood “big data” to be about analysis for data that’s really messy or where you don’t know the right questions or queries to make — analysis that can help you find patterns, anomalies, or new structures amidst otherwise chaotic or complex data points …” said Philip Ashlock, Chief Architect, Data.gov.
Big data is the broad name given to challenges and opportunities we have as data about every aspect of our lives becomes available. It’s not just about data though; it also includes the people, processes, and analysis that turn data into meaning,” said Josh Ferguson, Chief Technology Officer, Mode Analytics.
Big data means data that cannot fit easily into a standard relational database,” said Hal Varian, Chief Economist, Google.
Sign up for the free insideAI News newsletter.
