The industrial data revolution: What founders got wrong

In February 2010, The Economist published a report called “Data, data everywhere.” Little did we know then just how simple the data landscape actually was. That is, comparatively speaking, when you consider the data realities we’re facing as we look to 2022.

In that Economist report, I spoke about society entering an “Industrial Revolution of Data,” which kicked off with the excitement around Big Data and continues into our current era of data-driven AI. Many in the field expected this revolution to bring standardization, with more signal and less noise. Instead, we have more noise, but a more powerful signal. That is to say, we have harder data problems with bigger potential business outcomes.

And, we’ve also seen big advances in artificial intelligence. What does that mean for our data world now? Let’s take a look back at where we were.

At the time of that Economist article, I was on leave from UC Berkeley to run a lab for Intel Research in collaboration with the campus. We were focused all the way back then on what we now call the Internet of Things (IoT).

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