COVID19 and New Life

I’ve been doing a ton of writing and speaking, just not here. My first post on Medium is on COVID-19 myths and has a ton of links to reliable data sources to help dispel them. I’ve been writing some on the Vertica blog, doing a few projects for O’Reilly, and I’ve been writing my usual web content and technical architecture papers. But the main thing I’ve spent my time on in the last couple of years is public speaking. I was set to travel 5 weeks out of the last six to speak at conferences. That didn’t exactly happen.

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Data protection concept art

Data-Centric Security Rules

I just attended the Cybersecurity Summit in Dallas for the first time. I spoke a little on a small panel with a couple of customers about Voltage SecureData and Format Preserving Encryption (FPE). Then I got to go to other presentations and learned a lot. Probably the number one presentation that stuck with me, was Sid Dutta of Worldpay, the presenter who put the words “You will be breached!!” with double exclamation points on his slides, and said, “There are two kinds of enterprises, those who have been breached and know about it, and those who don’t know about it.”

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Paige Roberts presenting to full room with Zynga case study slide showing

DBTA Data Summit – The Rise of DataOps

The recent DBTA Data Summit provided a lot to think about. I did a short talk in the “Analytics in Action” track about how data analysts, architects and engineers can turn the endless waves of disruption we keep getting hit with into opportunities to boost bottom line. There were some very cool talks by other folks as well. For me, the highlights of the conference were Michael Stonebraker’s keynote, and the Data Kitchen folks diving into the principles of DataOps.

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Davin Potts, CEO Appliomics, Founder KNIME, Core Python Commiter

One on One with Davin Potts

At the recent Data Day Texas event, I sat down with Davin Potts, who I have known for many years, and had a long conversation about a wide variety of subjects. Over on the Vertica blog, I broke the conversation into chunks, but I wanted to put it all together in one place so you can see what we chatted about end to end. So, here’s all of it, from machine learning to open source, from Python to Knime, and why the heck DO we move data out of a database to analyze it?

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