Ibm Analytics Insights Podcasts

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Suj Perepa and Richard Darden. Suj is a distinguished engineer and specializes AI, machine learning technology in the financial sector.  Suj also has been a lead for security programs and a member of the IBM Academy of Technology leadership team. Richard is a distinguished engineer in digital human evangelism for North America government and a distinguished engineer at IBM in Cloud and Cognitive for the public sector and a former chief architect on federal government agencies.   Show Notes6:30 – What is a data framework?9:16 – What is framework?11:00 – Governance and people14:15 – Process and architecture19:15 – Bringing it al

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Kristen Summers who is a distinguished Engineer in Cloud and Cognitive Expert Labs. Kristen has worked in Artificial Intelligence and Data Science, PHD in Computer Science, and leads Data Science within our Expert Labs,  Show Notes2: 08 - More time needs to be spend on culture and talent management.3:55 - What does data driven culture mean?8:49 – What do you see driving fundamental culture?11:14 - What common tool do we have?12:55 – What is communicate about data?14:42 – How do you know you’re doing it well?17:29 - How do you define AI talent?23:18 - Describe a Data Scientist?27:25 - Common Organizational Structures 31:49 - Ho

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Lynne Snead. Lynne is the founder of Talent Evolution Systems, a behavioral analyst, consultant, training specialist, speaker, coach. Lynne has a back ground in Educational Psychology, and has specialized in organizational performance for over 20 years. Lynne is one of the original Franklin Covey co-authors, has a best seller, she created Franklin Covey’s signature Project Development process and programs, worked directly with Stephen R Covey Senior and Stephen MR Covey Junior. Lynne started her own company in 2003.Show Notes3:40 – Any advice on soft skills and hard skills?8:35 – Telltale signs such as stress10:40 – Settings g

Send us a textHosted by Al Martin, VP, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Lynne Snead. Lynne is the founder of Talent Evolution Systems, a behavioral analyst, consultant, training specialist, speaker, coach. Lynne has a back ground in Educational Psychology, and has specialized in organizational performance for over 20 years. Lynne is one of the original Franklin Covey co-authors, has a best seller, she created Franklin Covey’s signature Project Development process and programs, worked directly with Stephen R Covey Senior and Stephen MR Covey Junior. Lynne started her own company in 2003.Show Notes9:08 - Soft skills vs hard skills14:18 - What would you call soft skills?17:05 - Skills and culture19:03 – Can you change culture?22:15 – Behavioral stylesConnect with the TeamProducer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host

Send us a textIn part 2 of this two-part series, host Al Martin welcomes back Rob Thomas, GM of IBM Data and AI. The conversation ranges across the latest trends in enterprise analytics, how to tell the truth from the hype, and Rob’s own strategies for staying current, connected, and engaged in this fast-changing space.----------------------------Show Notes00:00 - Missed part 1? Catch up with the conversation here.00:05 - Check us out on YouTube and SoundCloud. 00:10 - Connect with Producer Steve Moore on LinkedIn and Twitter. 00:15 - Connect with Producer Liam Seston on LinkedIn and Twitter. 00:20 - Connect with Producer Rachit Sharma on LinkedIn. 00:25 - Connect with Host Al Martin on LinkedIn and Twitter. 00:52 - Connect with Rob Thomas on LinkedIn and Twitter.01:02 - Check out Rob's article on Watson Anywhere here. 02:03 - There is now proof that quantum computing can now boost machine learning! Read more here.05:17 - Your team needs a compass, not a map.10:00 - Warren Buffet and Mark Cuban agree, re

Send us a textRob Thomas, leader of IBM’s Data and AI division, talks with host Al Martin about the need to de-mystify AI. In particular, Rob recommends a "fail fast" approach to data science: run wide-ranging but short-term experiments — and expect disappointment on the way to insight. This episode offers a host of such suggestions, plus thoughtful leadership advice and tips for motivation. Part 1 of 2.---------------------------Show Notes00:00 - Check us out on YouTube and SoundCloud. 00:10 - Connect with Producer Steve Moore on LinkedIn and Twitter. 00:15 - Connect with Producer Liam Seston on LinkedIn and Twitter. 00:20 - Connect with Producer Rachit Sharma on LinkedIn. 00:25 - Connect with Host Al Martin on LinkedIn and Twitter. 00:55 - Connect with Rob Thomas on LinkedIn and Twitter.04:01 - Discover what big data and A.I. have in store. 06:22 - Learn more about IBM's Think conference here.06:48 - Read more on Watson anywhere here.10:24 - There is no A.I. without I.A.23:21 - Check out Al&a

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Claude Yusti. Claude is a Partner in IBM Global Business Services and is responsible for leading the Watson AI and Data Platform Practice for Public Sector. His primary clients are in Health and Human Services. He has over 30 years of experience in the Government and Healthcare industries and has worked with a number of industry. Show Notes2:00 – What questions do government and health care have?8:10 – How different are government and health care?12:40 - ROI within government and health care.cayusti@us.ibm.comClaude Yusti - LinkenIn http://www.businessofgovernment.org/bio/claude-yusti Connect with the TeamPr

Send us a textAbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Claude Yusti. Claude is a Partner in IBM Global Business Services and is responsible for leading the Watson AI and Data Platform Practice for Public Sector. His primary clients are in Health and Human Services. He has over 30 years of experience in the Government and Healthcare industries and has worked with a number of industry. Show Notes6:19 – Working with government9: 58 - On what context are you defining AI?11:04 – How do you see the protection of data?18:05 – Use cases25:01 – Skills, security, data set control and how the government differs from private sector? Claude Yusti - LinkenIn Connect with the TeamProducer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. Want to be featured as a gu

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Kush Varshney who is a Distinguished Research Staff Member and Manager of IBM Research and leads the Machine Learning group in the Foundations Trustworthy AI and the Co-Founder of IBM Science for Social Good. Kush has a history in Electrical Computer Engineering and a PHD at MIT.  Show Notes1:32 – Kush’s history6:36 – Is there such a thing as trust worthy AI?14:46 – Are we going to let AI make decisions?19:57 – Have you worked on any government projects? 21:41 – Government datasets governance 24:13 – Steps to invest in trust and fairness25:54 – What is Science for Social Good27:25 – Where will AI be in 3 yea

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Paul Zikopoulos. Paul is VP of Cognitive BigData Systems. Paul has written numerous books, and is a professional and award winning speaker. Show Notes5:39 – Paul’s experience 9:07 – Paul’s new book12:00 – What do you mean by “Until you don’t”?13:25 – What about systems GPUs?15:42 – What should I be thinking?18:07 – What else are you working on? 22:11 – Time management tips31:30 – Twitter commentConnect with the TeamProducer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. The AI LadderWant to be featured as a guest on Making Data Simple? Reach out to us at

Send us a textHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. Want to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. Abstract This week on Making Data Simple, we have a returning guest Dr. Kyu Rhee VP & Chief Health Officer IBM and IBM Watson Health, discussing the Covid-19 pandemic and how we prepare and react individually and as a country. What can we do for ourselves and how this pandemic affects the economy. And when do we see a light at the end of the tunnel.Show Notes1. https://www.ibm.com/blogs/watson-health/author/kyurhee/2. https://www.ibm.com/impact/covid-19/Connect with the TeamProducer Kate Brown - LinkedIn.Producer Michael Sestak - LinkedIn.Producer Meighann Helene - LinkedIn.Host Al Martin - LinkedIn and Twitter.Additional resources: IBM Watson Health CO

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Nancy Hensley, Nancy is currently the Chief Marketing and Product Officer for Stats Perform. Nancy was the Chief Digital Officer at IBM. Show Notes1:37 – Nancy’s bio3:10 - Are we talking Money Ball?5:52 - On Base percentage7:08 – Analyse examples 10:02 – Do you control the data?11:24 – Out there statistics14:12 - Can analytics go to far?17:35 – Real time analysis18:45 – Covid and sports21:15 – Your role in sports betting22:50 – What’s the most fascinating thing you’ve learned?25:23 – What’s the future?Website - Stats PerformMoney BallStats Perform - Twitter Bill James – Baseball Abstract The Analyst   Connec

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Lisa Palmer. Lisa is currently pursuing her doctorate in Artificial Intelligence, Chief Technical Advisor with Splunk Technologies. Lisa also was a professor at Southern Nazarene University, Tara Data Global Accounts Strategist, and then VP and America’s Regional Manager for Gartner.      Show Notes1:30 – Lisa’s background6:16 – What is your Brand10: 06 - Pros and cons of AI Intelligence12:14 – Policing AI15:40 – Does bias worry you20:00 - What is flipping to data leadership23:55 – What are you working on27:07 – Why is pursuing your doctorate important to you28:38 – What’s your advice for other leaders30:37

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Dale Davis Jones, who is an IBM Vice President and Distinguished Engineer in Global Technology Services, where she leads the GTS IT Architect community and Client Innovation. We also have Hai-Nhu Tran, who is the Senior Manager of Content of Design in Data and AI at IBM. Hai-Nhu and her team are responsible for the technical content experience for a large portfolio of products and platforms. Show Notes11:43 - What is the context and how did you get involved?17:10 - How do you define success?19:40 - Are you focused on IT language?25:03 - How do you know you’re doing it right?32:30 - What decision have already

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Kathy Parks. Kathy worked at IBM and is now an owner and independent Angel Investor. Kathy started her career in publishing and then transitioned over to Kurzweil Computer Products working on reading machine for the blind. Kathy then moved to Interleaf working on publishing products, then to QA and Project Management. Kathy then moved to Rational Software and in 2003 Rational was bought by IBM. Show Notes2:10 - How do you go from publishing to project management?3:15 - How did you transition to Angel Investing?5:58 - What’s at the core7:06 - What is Angel Investing12:40 - Is there a formula that you use?17:2

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Oliver Claude Portfolio Offering Manager for Data and AI and Oliver is a Data Governance expert. Oliver also worked as a Chief Marketing Officer, VP and Chief Solution Owner, Solution Management, and Consulting, Al and Oliver discuss Data Governance and Data Ops and how it all fits into your business.  Show Notes2:50 - What is the definition of Data Governance?4:06 - What is Data Ops?4:40 - What is IBM doing with Data Ops?5:16 - How have we automated our tools?6:58 - What is better red or white wine?7:33 - What is the future of Data Governance?9:37 - How is Data Governance and Data Ops related to AI?11:06 -

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Lynne Snead. Lynne is the founder of Talent Evolution Systems, a behavioral analyst, consultant, training specialist, speaker, coach, Lynne has a back ground in Educational Psychology, and has specialized in organizational performance for over 20 years. Lynne is one of the original Franklin Covey co-authors, has a best seller, she created Franklin Covey’s signature Project Development process and programs, worked directly with Stephen Covey.Show Notes2:25 – Can data define behavior in someone?7:19 – How do you complete an assessment?9:46 – Attributes of assessments20:25 – Coaching advice Lynne Snead - Linked

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Lynne Snead. Lynne is the founder of Talent Evolution Systems, a behavioral analyst, consultant, training specialist, speaker, coach, Lynne has a back ground in Educational Psychology, and has specialized in organizational performance for over 20 years. Lynne is one of the original Franklin Covey co-authors, has a best seller, she created Franklin Covey’s signature Project Development process and programs, worked directly with Stephen Covey.1:30 – Lynne talks about her background5:40 – Lynne’s coaching specialty and mission statement10:30 – Why don’t all leaders have coaches?12:08 – Why do you differentiate

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Amy McDermott. Amy is a science journalist at Front Matter, the magazine section of PNAS (Proceedings of the National Academy of Sciences), where she covers new and emerging research. Her background spans ecology and journalism: she has an MA in conservation biology from Columbia University and a graduate certificate from the UC Santa Cruz Science Communication Program. Show Notes4:20 - Amy’s background7:25 – Amy summaries the stories on fires11:21 – What does the data suggest about fires?12:04 – Are there computer models on fires? 17:35 – Real world example of how models are used19:44 – How accurate is the

Send us a textWant to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Dr. Kayla Lee Growth Product Manager, Community Partnerships at IBM Quantum & Qiskit. Dr. Kayla Lee works with innovation teams across industries to understand how they can using new and emerging technologies to solve their business challenges. In her role, she serves as a bridge between business and science to help drive value for enterprise clients. Her primary focus is the new model of computation, quantum computing, working with clients to understand potential applications, prioritize use cases, and build a business strategy to prepare for the future of computing. Al and Dr. Lee try and help us under