In this podcast, Venu Vasudevan(@ProcterGamble) talks about the best practices of creating a research-led data-driven data science team. He walked through his journey of creating a robust and sustained data science team, spoke about bias in data science, and some practices leaders and data science practitioners could adopt to create an impactful data science team. This podcast is great for future data science leaders and practitioners leading organizations to put together a data science practice.

Timeline: 0:29 Venu's jouney. 11:18 Venu's current role in PNG. 13:11 Standardization of technology and IoT. 17:18 The state of AI. 19:46 Running an AI and data practice for a company. 22:30 Building a data science practice in a startup in comparison to a transnational company. 24:05 Dealing with bias. 27:32 Culture: a block or an opportunity. 30:05 Dealing with data we've never dealt with before. 32:32 Sustainable vs. disruption. 36:17 Starting a data science team. 38:34 Data science as an art of doing and science of doing business. 41:37 Tips to improve storytelling for a data practitioner. 43:30 Challenges in Venu's journey. 44:55 Tenets of a good data scientist. 47:27 Diversity in hiring. 50:50 KPI's to look out for if you are running an AI practice. 51:37 Venu's favorite read.

Venu's Recommended Read: Isaac Newton: The Last Sorcerer - Michael White http://amzn.to/2FzGV0N Against the Gods: The Remarkable Story of Risk - Peter L. Bernstein http://amzn.to/2DRPveU

Podcast Link: https://futureofdata.org/venu-vasudevan-venuv62-proctergamble-on-creating-a-rockstar-data-science-team-futureofdata/

Venu's BIO: Venu Vasudevan is Research Director, Data Science & AI at Procter & Gamble, where he directs the Data Science & AI organization at Procter & Gamble research. He is a technology leader with a track record of successful consumer & enterprise innovation at the intersection of AI, Machine Learning, Big Data, and IoT. Previously he was VP of Data Science at an IoT startup, a founding member of the Motorola team that created the Zigbee IoT standard, worked to create an industry-first zero-click interface for mobile with Dag Kittlaus (co-creator of Apple Siri), created an industry-first Google Glass experience for TV, an ARRIS video analytics and big data platform recently acquired by Comcast, and a social analytics platform leveraging Twitter that was featured in Wired Magazine and BBC. Venu held a Ph.D. (Databases & AI) from Ohio State University and was a Motorola’s Science Advisory Board (top 2% of Motorola technologists). He is an Adjunct Professor at Rice University’s Electrical and Computer Engineering department and was a mentor at Chicago’s 1871 startup incubator.

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers, and lead practitioners to discuss their journey to create the data-driven future.

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FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy

Early astronomers could see several of the planets with the naked eye. The invention of the telescope allowed for further understanding of our solar system. The work of Isaac Newton allowed later scientists to accurately predict Neptune, which was later observationally confirmed exactly where predicted. It seemed only natural that a similar unknown body might explain anomalies in the orbit of Mercury, and thus began the search for the hypothesized planet Vulcan. Thomas Levenson's book "The Hunt for Vulcan" is a narrative of the key scientific minds involved in the search and eventual refutation of an unobserved planet between Mercury and the sun. Thomas joins me in this episode to discuss his book and the fascinating story of the quest to find this planet. During the discussion, we mention one of the contributions made by Urbain-Jean-Joseph Le Verrier which involved some complex calculations which enabled him to predict where to find the planet that would eventually be called Neptune. The calculus behind this work is difficult, and some of that work is demonstrated in a Jupyter notebook I recently discovered from Paulo Marques titled The-Body Problem. Thomas Levenson is a professor at MIT and head of its science writing program. He is the author of several books, including Einstein in Berlin and Newton and the Counterfeiter: The Unknown Detective Career of the World’s Greatest Scientist. He has also made ten feature-length documentaries (including a two-hour Nova program on Einstein) for which he has won numerous awards. In his most recent book "The Hunt for Vulcan", explores the century spanning quest to explain the movement of the cosmos via theory and the role the hypothesized planet Vulcan played in the story. Follow Thomas on twitter @tomlevenson and check out his blog athttps://inversesquare.wordpress.com/. Pick up your copy of The Hunt for Vulcan at your local bookstore, preferred book buying place, or at the Penguin Random House site.

Minitab Cookbook is your hands-on guide to mastering Minitab, a powerful tool for statistical analysis. With over 110 practical recipes, this book will guide you through data organization, analysis, and graphing techniques, equipping you with skills to tackle diverse real-world data problems. What this Book will help me do Master data importation into Minitab and preprocessing workflows. Generate and customize impactful visualizations for your datasets. Apply statistical techniques such as hypothesis testing in Minitab. Perform regression analysis and understand model outcomes. Utilize Minitab's advanced tools for process capability and quality improvement. Author(s) Isaac A Newton, an experienced statistician, has years of professional expertise in statistical analysis and its applications across various domains. Passionate about data visualization and statistical modeling, he aims to make intricate statistical topics approachable and practical with Minitab. His engaging writing style brings clarity to complex techniques. Who is it for? This book is perfect for statisticians and professionals with basic statistical knowledge looking to harness the capabilities of Minitab for their projects. Ideal for both newcomers to Minitab and those seeking advanced recipes to improve their efficiency. Whether you're analyzing simple datasets or complex statistical phenomena, this book will be a valuable resource. Educational professionals and students can also benefit greatly from its clear, practical approach to learning Minitab.