Why Amazon thinks big data was made for the cloud

Grazed from GigaOM. Author: Derrick Harris.

According to Amazon Web Services Chief Data Scientist Matt Wood, big data and cloud computing are nearly a match made in heaven. Limitless, on-demand and inexpensive resources open up new worlds of possibility, and a central platform makes it easy for communities to share huge datasets.

For Amazon Web Services Chief Data Scientist Matt Wood, the day isn’t filled performing data alchemy on behalf of his employer; he’s entertaining its customers. Wood helps AWS users build big data architectures that use the company’s cloud computing resources, and then take what he learns about those users’ needs and turn them into products — such as the Data Pipeline Service and Redshift data warehouse AWS announced this week. He and I sat down this week at AWS’s inaugural Re: Invent conference and talked about many things, including what he’s seen in the field and where cloud-based big data efforts are headed. Here are the highlights…

The end of contstraint-based thinking

Not so long ago, computer scientists understood many of the concepts that we now call data science, but limited resources meant they were hamstrung in the types of analysis they could attempt to do. “That can be very limiting, very constraining when you’re working with data,” Wood said…

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