Podcasts about schmarzo

On this edition of StrongbyScience, the shows producer, Brendon Rider, talks with Max about a range of topics, including a live Q&A with Max's followers.

On this edition of StrongbyScience, Max speaks at the Rocky Mountain Strength & Conditioning Summit at Colorado State University. Presentation (00:01:28 - 01:09:49), question & answer (01:09:49 - 01:16:24).

On this edition of StrongbyScience, Max answers questions from listeners.

On this edition of StrongbyScience, Max talks about jumping higher (00:36), where to start with sport science (09:29), is power training only for athletes (15:44), allostatic load (21:12), and nutrient timing (25:30).

On this episode Max talks about the working effect of a muscle.

In this podcast, Bill Schmarzo talks about the ingredients of successful data science practice, team, and executives. Bill shared his insights on what some leaders in the industries are doing and some challenges seen in the successful deployment. Bill shared his key take on ingredients for some of the successful hires. This podcast is great for growth mindset executives willing to learn about creating a successful data science practice. Timeline: 0:29 Bill's journey. 5:05:00 Bill's current role. 7:04 Data science adoption challenges for businesses. 9:33 The good side of data science adoption. 11:22 How is data science changing business. 14:34 Strategies behind distributed IT. 18:35 Analysing the current amount of data. 21:50 Who should own the idea of data science? 24:34 The right background for a CDO. 25:52 Bias in IT. 29:35 Hacks to keep yourself bias-free. 31:58 Team vs. tool for putting together a good data-driven practice. 34:54 Value cycle in data science. 37:10 Maturity model. 39:17 Convincing culture heavy businesses to adopt data. 42:47 Keeping oneself sane during the technological disruption. 46:20 Hiring the right talent. 51:46 Ingredients of a good data science hire. 56:00 Bill's success mantra. 59:07 Bill's favorite reads. 1:00:36 Closing remarks. Bill's Recommended Read: Moneyball: The Art of Winning an Unfair Game by Michael Lewis http://amzn.to/2FqBFg8 Big Data MBA: Driving Business Strategies with Data Science by Bill Schmarzo http://amzn.to/2tlZAvP Podcast Link: https://futureofdata.org/schmarzo-dellemc-on-ingredients-of-healthy-datascience-practice-futureofdata-podcast/ Bill's BIO: Bill Schmarzo is the CTO for the Big Data Practice, where he is responsible for working with organizations to help them identify where and how to start their big data journeys. He's written several white papers, is an avid blogger, and is a frequent speaker on the use of Big Data and data science to power the organization's key business initiatives. He is a University of San Francisco School of Management Fellow, where he teaches the "Big Data MBA" course. Bill has over three decades of experience in data warehousing, BI, and analytics. Bill authored EMC's Vision Workshop methodology that links an organization's strategic business initiatives with their supporting data and analytic requirements and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute's faculty as the head of the analytic applications curriculum. Bill holds a master's degree in Business Administration from the University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science, and Business Administration from Coe College. 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. Wanna Join? If you or any you know wants to join in, Register your interest @ http://play.analyticsweek.com/guest/ Want to sponsor? Email us @ info@analyticsweek.com Keywords: #FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Dell EMC’s Big Data Practice. As a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Big Data is a term. The adjective ‘big’ has no meaning. Most companies are interested in looking at the ‘boat load of data’ they have but are not sure what to do with it. Right now, companies are only looking at the data to see ‘what happened’. “The biggest challenge from IT side and business side is to understand how they can understand data to effectively power their business model.” Dell is using data to do predictive maintenance on their equipment. The goal is to fix devices before they break. They do this with employees and health care. “We try to drink our own champagne – use data internally, so we can be credible in the marketplace.” Why have data if you aren’t going to use it? “Data by itself is a glob of nothing. You need to have an analytic strategy to tell what data is needed.” Organizations need to know what problems they are trying to accomplish then can make analytics on those. If you know the problem to solve, you know the analytics and data you need. Then it becomes easy. Ask the questions first. Business has to drive IT. Data is a business conversation about economics. Then you can exploit the use of data. There is a new position, the Chief Data Officer. It’s a good idea, but there has been poor execution. What has been happening is taking a CIO and giving them a new title of CDO. However, it should be the Chief Data Monetization Officer. The job is to determine how to monetize the data you have available. This should be an economics person rather than IT person. Schmarzo’s advice for people who are thinking about big data? Business people: Read his book written for business people. Also, check out his blog as he frequently blogs about big data. He recently wrote about how to become intelligent like Netflix. Everyday people: You need to understand the basics. Start reading, attending the free online classes, read blogs. Begin to understand what is machine learning and AI is all about. Don’t be afraid; just spend 15 minutes a day to become more familiar. What you will learn in this episode: ● Why the term Big Data is a misnomer ● How Dell is using data ● The ‘mindset’ of data ● Why big data is about economics, not technology ● How much of a CIO’s background should be in technology vs. business and economics ● What role data plays in AI, wearables and machine learning   Links from the episode: ● Blogs: infocus.emc.com/author/william_schmarzo/ (Blog) ● LinkedIn: linkedin.com/in/schmarzo

Bill Schmarzo is the CTO of EMC's Big Data Consulting Practice and a frequent industry speaker, a blogger, a professor at the University of San Francisco School of Management as well as an author. Schmarzo wrote "Big Data MBA: Driving Business Strategies with Data Science" and "Big Data: Understanding How Data Powers Big Business". Show notes at http://hellotechpros.com/bill-schmarzo-people/ Key Takeaways The companies who are successful with Big Data addressed the cultural or people issues. How do we get people engaged in the process so that we're delivering the analytics in a way that is actionable to our stakeholders? Many companies tend to start with implementing Hadoop and then waiting for magic to happen. It doesn't happen. Data science is really identifying the variables and metrics that MIGHT be a better predictor of performance. "Might" is a license to be wrong and in many companies the idea of wrong is bad. In the BI space, the IT departments over promised and under deliveredwhich has lead business leaders to be skeptical of Big Data initiatives. You have to have a tight alignment between the business and IT to ensure that we are working on the right problems. Pick a topic / problem that business users find is important, focus on strategic business initiatives. Create a link between business and data scientists. Create a culture of creativity across the whole organization. Creativity is a contagious event. All ideas are worthy of consideration. We want people to be unafraid to be creative and sharing their ideas even if they may not work. The best ideas come from front line. Most large organizations struggle with protecting their own fiefdoms which leads to data silos. Big Data is not about big, its about small. Learn as much as possible about individual person, event and situation instead of looking at the average of the data. Aggregated data is the devil. You need to work with raw to serve the individual. Big Data initiatives tend to fail because the teams are focused on too many opportunities instead of being focused and priortizing the most important business problems. Focus on one decision which has high value and high feasibility. Big Data is a team sport. We need everyone involved, including the business, the IT and the data scientists. Success breeds success. Quick wins will catch the attention of other people and build a grassroots movement.