Janet George's guest appearances

Janet George

Just Wanna Quilt

Women in Data Science

Data Science Leaders

Jacquie Gering

Tula Pink

Roark Dowell

Andrea Tsang Jackson

Stephanie Kendron

Kristin Esser

Tammy Silvers

Ali Smith

Heather Grant

Jo Westfoot

Michael McCormick

Dora Cary

Patty Dudek

Alex Anderson

Toni Smith

OwlTail

Is your team mining all available data to inform your business strategy and grow revenue? Is your company prepared to compete against others who are? If you’re like most, the answer is probably no. How can you future-proof your organization and take steps toward an autonomous enterprise? Janet George is an enterprise AI leader and author with experience across companies including Oracle, Apple, Accenture, Yahoo!, eBay, and more. She joins the show to discuss the meaning of autonomous enterprise and the process required for true transformation. We discuss: What is an autonomous enterprise? Where are companies falling short in their data transformation? The investment and first steps required on the transformation journey How to prioritize data projects for a larger impact on revenue  Tune in on Apple Podcasts, Spotify, our website, or wherever you listen to podcasts. Can’t see the links above? Just visit domino.buzz/podcast for helpful links from each episode.

Is your team mining all available data to inform your business strategy and grow revenue? Is your company prepared to compete against others who are? If you’re like most, the answer is probably no. How can you future-proof your organization and take steps toward an autonomous enterprise? <a href="https://www.linkedin.com/in/janet-george-a3136/" rel="nofollow" target="_blank">Janet George</a> is an enterprise AI leader and author with experience across companies including Oracle, Apple, Accenture, Yahoo!, eBay, and more. She joins the show to discuss the meaning of autonomous enterprise and the process required for true transformation. We discuss: <ul><li>What is an autonomous enterprise?</li> <li>Where are companies falling short in their data transformation?</li> <li>The investment and first steps required on the transformation journey</li> <li>How to prioritize data projects for a larger impact on revenue</li> </ul> Tune in on <a href="https://podcasts.apple.com/us/podcast/data-science-leaders/id1564587119" rel="nofollow" target="_blank">Apple Podcasts</a>, <a href="https://open.spotify.com/show/0zJgKGIHZzJG1VgSDHNojP" rel="nofollow" target="_blank">Spotify</a>, our <a href="https://www.dominodatalab.com/data-science-leaders-podcast/" rel="nofollow" target="_blank">website</a>, or wherever you listen to podcasts. Can’t see the links above? Just visit <a href="http://domino.buzz/podcast" rel="nofollow" target="_blank">domino.buzz/podcast</a> for helpful links from each episode.

Data in the DNA: Breaking Down the Autonomous Enterprise (Janet George, Enterprise AI Leader & Author)

Janet is amazing.  Her videos and Facebook comments help hundreds of us navigate the software, Quilter's Creative Touch, used in Grace machines and so many others.   This was recorded before the upgrade to QC5.

Janet George teaches us all how to use Quilter's Creative Touch

“Fail fast” has become something of a mantra in Silicon Valley. But Janet George, the chief data officer of data storage giant Western Digital, has an amendment to that conventional wisdom: “Fail privately.”She suggests that failing privately allows you to open yourself up to discovery and exploration in a safe setting where you are able to take risks. “Carve out time for yourself so you can fail privately. So, you take 20 percent of your time in big initiatives you feel you can really contribute to, but take 20 percent of your time [(where you can])fail privately.” George, who has worked for some of the most important companies in the technology industry, shared this piece of advice, her career trajectory and the role of data science in the storage industry for the Women in Data Science podcast at Stanford University. Although the fear of failure is natural, it should never become a reason to avoid risk, she says. Taking an executive role at a storage company was a risk for George because she knew little about manufacturing before and. “I had to learn deeply about the device physics domain,.” she says. She became familiar with arcane matters like bit counts, failure rates, temperature testing and the impact of voltage on storage cells in order to ensure her success. Now in her fourth year at Western Digital, George continues to notice how much data science comes into play across the spectrum of the company’s business. From manufacturing to security and product development, “every aspect of mathematics, especially linear algebra, plays a very significant role,” she says. “When you think about the computations of scale, when you think about genetic algorithms, its applications, regression-type algorithms, or you even think about neural networks, it’s computationally heavy, it’s mathematically heavy.” Creating a die, essentially a mold, for a new storage device, for example, starts with tens of thousands of possible parameters. Data scientists at the company have to sift through a multitude of mathematical possibilities and discover the 20 or 25 most critical parameters. As the only woman at most executive meetings, George is wielding influence as a lone voice at the table, a skill honed over many years with important risks taken along the way. Her advice for aspiring data scientists: Build relationships and credibility within your organization and lead by example.

“Fail fast” has become something of a mantra in Silicon Valley. But Janet George, the chief data officer of data storage giant Western Digital, has an amendment to that conventional wisdom: “Fail privately.”She suggests that failing privately allows you to open yourself up to discovery and exploration in a safe setting where you are able to take risks. “Carve out time for yourself so you can fail privately. So, you take 20 percent of your time in big initiatives you feel you can really contribute to, but take 20 percent of your time [(where you can])fail privately.” George, who has worked for some of the most important companies in the technology industry, shared this piece of advice, her career trajectory and the role of data science in the storage industry for the Women in Data Science podcast at Stanford University. Although the fear of failure is natural, it should never become a reason to avoid risk, she says. Taking an executive role at a storage company was a risk for George because she knew little about manufacturing before and. “I had to learn deeply about the device physics domain,.” she says. She became familiar with arcane matters like bit counts, failure rates, temperature testing and the impact of voltage on storage cells in order to ensure her success. Now in her fourth year at Western Digital, George continues to notice how much data science comes into play across the spectrum of the company’s business. From manufacturing to security and product development, “every aspect of mathematics, especially linear algebra, plays a very significant role,” she says. “When you think about the computations of scale, when you think about genetic algorithms, its applications, regression-type algorithms, or you even think about neural networks, it’s computationally heavy, it’s mathematically heavy.” Creating a die, essentially a mold, for a new storage device, for example, starts with tens of thousands of possible parameters. Data scientists at the company have to sift through a multitude of mathematical possibilities and discover the 20 or 25 most critical parameters. As the only woman at most executive meetings, George is wielding influence as a lone voice at the table, a skill honed over many years with important risks taken along the way. Her advice for aspiring data scientists: Build relationships and credibility within your organization and lead by example.

Janet George | The Multifaceted World of Data Storage