Google Professional Cloud Architect Study Guide

Chapter 9. Data Analytics and Big Data on GCP: Piles of Data to Gold

I was sitting in a conference room in Denver a few years back, watching a VP of operations literally turn red in the face. Not embarrassed red or fighting mad red, but more the slow boil shade of frustrated red that only comes from dealing with data problems.

“We have all this data,” he said, waving his arms out toward the distance at some invisible pile of information floating somewhere outside the building, “Terabytes of it! Customer transactions, website clicks, inventory movements, and sensor readings from our manufacturing center, but asking a simple question like ‘What products are trending in the Southwest region this month?’ takes our DA team three days and an Excel spreadsheet that crashes twice.”

It took me a minute to figure out that DA stood for data analytics and not district attorney, but that’s because I watch too many true crime documentaries.

I couldn’t help but smile. Not because I enjoyed his pain (seriously though, what’s up with managers and Excel?), but because I’d heard this exact story a hundred times before. Companies all over the place are sitting on gold mines of information, but they’re digging it out with pickaxes and pans. What they need is some modern machinery.

“What if I told you,” I said, “that you could ask that question and get an answer in about 30 seconds?”

He looked at me like I’d just claimed I could turn water into wine. I mean, I’ve worked a miracle or two with data, ...