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Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons द्वारा प्रदान की गई सामग्री. एपिसोड, ग्राफिक्स और पॉडकास्ट विवरण सहित सभी पॉडकास्ट सामग्री Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons या उनके पॉडकास्ट प्लेटफ़ॉर्म पार्टनर द्वारा सीधे अपलोड और प्रदान की जाती है। यदि आपको लगता है कि कोई आपकी अनुमति के बिना आपके कॉपीराइट किए गए कार्य का उपयोग कर रहा है, तो आप यहां बताई गई प्रक्रिया का पालन कर सकते हैं https://hi.player.fm/legal
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Janet George | The Multifaceted World of Data Storage

31:20
 
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Manage episode 264308739 series 2706384
Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons द्वारा प्रदान की गई सामग्री. एपिसोड, ग्राफिक्स और पॉडकास्ट विवरण सहित सभी पॉडकास्ट सामग्री Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons या उनके पॉडकास्ट प्लेटफ़ॉर्म पार्टनर द्वारा सीधे अपलोड और प्रदान की जाती है। यदि आपको लगता है कि कोई आपकी अनुमति के बिना आपके कॉपीराइट किए गए कार्य का उपयोग कर रहा है, तो आप यहां बताई गई प्रक्रिया का पालन कर सकते हैं https://hi.player.fm/legal

“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.

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53 एपिसोडस

Artwork
iconसाझा करें
 
Manage episode 264308739 series 2706384
Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons द्वारा प्रदान की गई सामग्री. एपिसोड, ग्राफिक्स और पॉडकास्ट विवरण सहित सभी पॉडकास्ट सामग्री Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons या उनके पॉडकास्ट प्लेटफ़ॉर्म पार्टनर द्वारा सीधे अपलोड और प्रदान की जाती है। यदि आपको लगता है कि कोई आपकी अनुमति के बिना आपके कॉपीराइट किए गए कार्य का उपयोग कर रहा है, तो आप यहां बताई गई प्रक्रिया का पालन कर सकते हैं https://hi.player.fm/legal

“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.

  continue reading

53 एपिसोडस

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