Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted 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 Notes 2: 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 - How do you manage and grow AI talent? IBM Skills Academy     Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted 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 Notes 3:40 – Any advice on soft skills and hard skills? 8:35 – Telltale signs such as stress 10:40 – Settings goals  Connect with the Team Producer Kate Brown - LinkedIn Producer Steve Templeton - LinkedIn Host Al Martin - LinkedIn and Twitter

Books Thinking Fast and Slow  Financial Intelligence  Other notable names Brene Brown Judith Glaser Marshall Goodsmith Daniel Goleman

Lynne’s List of Recommended Leadership Books Leadership and Self Deception, Arbinger Institute7 Habits of Highly Effective People, Stephen R. Covey (Senior)5 Levels of Leadership, John Maxwell. What Got You Here Won’t Get You There, Marshall GoldsmithConversational Intelligence, Judith GlaserThe Speed of Trust, Stephen M.R. Covey (Junior) Emotional Intelligence, Daniel GolemanThe New Art of Managing People, Tony Alessandra and Phil HunsakerHow to Influence People, John MaxwellHumble Inquiry, Edgar H. Schein Humble Leadership, Edgar H. Schein and Peter ScheinLeadership is an Art, Max De PreeThe Secrets to Winning at Office Politics, Marie G. McIntyreThe Power of Focus, Jack Canfield, Mark Victor Hansen, Les HewittThe Power of Self-Confidence, Brian TracyWant to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Hosted 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 Notes 9:08 - Soft skills vs hard skills 14:18 - What would you call soft skills? 17:05 - Skills and culture 19:03 – Can you change culture? 22:15 – Behavioral styles Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Rob 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 Notes 00:00 - 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's talk at Think 2019 with Jeff Jonas here. 23:51 - Check out this interview with Rob Thomas at Think 2019 here. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted 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 Notes 2:00 – 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. [email protected] Claude Yusti - LinkenIn  http://www.businessofgovernment.org/bio/claude-yusti 

Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Use Predictive Analytics to Uncover Hidden Patterns and Correlations and Improve Decision-Making Using predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data and leverage these insights to improve many key business decisions. In this thoroughly updated guide, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for both business professionals and students. Delen provides a holistic approach covering key data mining processes and methods, relevant data management techniques, tools and metrics, advanced text and web mining, big data integration, and much more. Balancing theory and practice, Delen presents intuitive conceptual illustrations, realistic example problems, and real-world case studiesincluding lessons from failed projects. It is all designed to help you gain a practical understanding you can apply for profit. * Leverage knowledge extracted via data mining to make smarter decisions * Use standardized processes and workflows to make more trustworthy predictions * Predict discrete outcomes (via classification), numeric values (via regression), and changes over time (via time-series forecasting) * Understand predictive algorithms drawn from traditional statistics and advanced machine learning * Discover cutting-edge techniques, and explore advanced applications ranging from sentiment analysis to fraud detection .

Send us a text Abstract Hosted 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 Notes 6:19 – Working with government 9: 58 - On what context are you defining AI? 11:04 – How do you see the protection of data? 18:05 – Use cases 25:01 – Skills, security, data set control and how the government differs from private sector?  Claude Yusti - LinkenIn  Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Thomas Dietterich ( @tdietterich ) on Understanding the Depth of AI #FutureOfData #Leadership #Podcast

In this podcast Thomas Dietterich(@tdietterich) Distinguished Professor Emeritus @ Oregan State University sat with Vishal @ AnalyticsWeek to discuss the depth of AI. in This session Tom shared the current state, limitations and future of AI. He shared areas where AI is relevant and which areas are still seeking more testing for AI adoption. He also shared some of the pitfalls with current AI framework, area of selective bias, knowing context etc. This is a great session for anyone seeking to learn about the World of AI.

Thomas's Recommended Read: Army of None: Autonomous Weapons and the Future of War by Paul Scharre https://amzn.to/2CnoA94

Podcast Link: iTunes: http://math.im/itunes Youtube: http://math.im/youtube

Thomas's BIO: Thomas Dietterich has devoted his career to research in machine learning starting from the very first machine learning workshop in 1980. Along the way, he has been involved in four startup companies: Arris Pharmaceutical, MusicStrands, Smart Desktop, and (currently) BigML. He has made important contributions to learning with weak labels, ensemble methods, hierarchical reinforcement learning. and robust artificial intelligence. He was founding President of the International Machine Learning Society (which runs the International Conference on Machine Learning) and President of the Association for the Advancement of Artificial Intelligence. He has served on numerous government advisory bodies and currently is a member of the steering committee of the DARPA ISAT group. Dietterich earned his bachelor's degree from Oberlin College, his M.S. from the University of Illinois, and his PhD from Stanford University. He is a Fellow of the ACM, AAAI, and AAAS.

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers and lead practitioners to come on show and discuss their journey in creating the data driven future.

Wanna Join? If you or any you know wants to join in, Register your interest by mailing us @ [email protected]

Want to sponsor? Email us @ [email protected]

Keywords: FutureOfData,

DataAnalytics,

Leadership,

Futurist,

Podcast,

BigData,

Strategy

In this podcast, Nathan Furr(@nathan_furr) talks about leading transformation. He shares some of the crucial ingredients of transformational leaders. He sheds some light on how businesses could improve their storytelling to get the transformation agenda across. He shares some cool tips and tricks that help leaders plan for a transformation across data-driven and disruptive times.

Timeline: 1:39 Nathan's journey. 4:49 Nathan's current role. 13:55 Transforming legacy old company. 21:52 The right moment for companies to think about data transformation. 26:38 Using comic books to share transformational stories. 34:32 Who's the most responsible person in an organization for transformation? 39:13 Qualities a leader must have for bringing in transformational change. 43:40 Nathan's success mantra. 47:57 Nathan's favorite reads. 50:29 Closing remarks.

Nathan's Recommended Read: East of Eden (Penguin Twentieth-Century Classics) by John Steinbeck, David Wyatt https://amzn.to/2S9MHA0

Nathan's Books The Innovator's Method: Bringing the Lean Start-up into Your Organization by Nathan Furr, Jeff Dyer, Clayton M. Christensen https://amzn.to/2TeadJE Leading Transformation: How to Take Charge of Your Company's Future by Nathan Furr, Kyle Nel, Thomas Zoega Ramsey https://amzn.to/2CTw16z Nail It then Scale It: The Entrepreneur's Guide to Creating and Managing Breakthrough Innovation: The lean startup book to help entrepreneurs launch a high-growth business by Nathan Furr, Paul Ahlstrom https://amzn.to/2UfTpSC

Podcast Link: https://futureofdata.org/leading-transformation-through-data-driven-times-nathan_furr-insead-futureofdata-podcast/

Nathan's BIO: Nathan Furr is a professor of strategy and innovation at INSEAD in Paris and a recognized expert in innovation and technology strategy. He has multiple books and articles published by outlets such as Harvard Business Review and MIT Sloan Management Review, including his most recent best-selling book, “The Innovator’s Method” (Harvard Business Review Press, September 2014), which won multiple awards from the business press. He has two forthcoming books from Harvard Business Review Press addressing 1) how companies lead transformation and 2) how innovators win support for their ideas.

Professor Furr has worked with leading companies to study and implement innovation strategies, including Google, Amazon, Citi, Deutsche Bank, Philips, Kimberly Clark, Solvay, and others. Professor Furr earned his Ph.D. from the Stanford Technology Ventures Program at Stanford University.

About #Podcast:

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

Wanna Join? If you or any you know wants to join in, Register your interest by emailing us @ [email protected]

Want to sponsor? Email us @ [email protected]

Keywords: FutureOfData,

DataAnalytics,

Leadership,

Futurist,

Podcast,

BigData,

Strategy

Millions of non-technical professionals and leaders want to understand Artificial Intelligence (AI) and Machine Learning (ML) — whether to improve their businesses, be more effective citizens, consumers or policymakers, or just out of sheer curiosity. Until now, most books on the subject have either been too complicated and mathematical, or have simply avoided the big picture by focusing on the use of specific software libraries. In , Doug Rose bridges the gap, offering today’s most accessible and useful introduction to AI and ML technologies — and what they can and can’t do. Artificial Intelligence for Business Rose begins by tracing AI’s evolution from the early 1950s to the present, illuminating core ideas that still drive its development. Next, he explores recent innovations that have reinvigorated the field by providing the “big data” that makes machine learning so powerful – innovations such as GPS, social media and electronic transactions. Finally, he explains how today’s machines learn by combining powerful processing, advanced algorithms, and artificial neural networks that mimic the human brain. Throughout, he illustrates key concepts with practical examples that help you connect AI, ML, and neural networks to specific problems and solutions. Step by step, he systematically demystifies these powerful technologies, removing the fear, bewilderment, and advanced math — so you can understand the new possibilities they create, and start using them.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted 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 Notes 1:32 – Kush’s history 6:36 – 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 fairness 25:54 – What is Science for Social Good 27:25 – Where will AI be in 3 years? 30:02 – White noise for the nose IBM for Social Good Trusting AI  Factfulness Trust Worthy Machine Learning (coming next year)     Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

This IBM® Redbooks® publication introduces and describes the IBM Elastic Storage® Server 5000 (ESS 5000) as a scalable, high-performance data and file management solution. The solution is built on proven IBM Spectrum® Scale technology, formerly IBM General Parallel File System (IBM GPFS). ESS is a modern implementation of software-defined storage, making it easier for you to deploy fast, highly scalable storage for AI and big data. With the lightning-fast NVMe storage technology and industry-leading file management capabilities of IBM Spectrum Scale, the ESS 3000 and ESS 5000 nodes can grow to over YB scalability and can be integrated into a federated global storage system. By consolidating storage requirements from the edge to the core data center — including kubernetes and Red Hat OpenShift — IBM ESS can reduce inefficiency, lower acquisition costs, simplify storage management, eliminate data silos, support multiple demanding workloads, and deliver high performance throughout your organization. This book provides a technical overview of the ESS 5000 solution and helps you to plan the installation of the environment. We also explain the use cases where we believe it fits best. Our goal is to position this book as the starting point document for customers that would use the ESS 5000 as part of their IBM Spectrum Scale setups. This book is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for delivering cost-effective storage solutions with ESS 5000.

Summary Building data products are complicated by the fact that there are so many different stakeholders with competing goals and priorities. It is also challenging because of the number of roles and capabilities that are necessary to go from idea to delivery. Different organizations have tried a multitude of organizational strategies to improve the success rate of these data teams with varying levels of success. In this episode Jesse Anderson shares the lessons that he has learned while working with dozens of businesses across industries to determine the team structures and communication styles that have generated the best results. If you are struggling to deliver value from big data, or just starting down the path of building the organizational capacity to turn raw information into valuable products then this is a conversation that you don’t want to miss.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it? I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. Go to dataengineeringpodcast.com/97things to add your voice and share your hard-earned expertise. When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $60 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Are you bogged down by having to manually manage data access controls, repeatedly move and copy data, and create audit reports to prove compliance? How much time could you save if those tasks were automated across your cloud platforms? Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud. Our comprehensive data-level security, auditing and de-identification features eliminate the need for time-consuming manual processes and our focus on data and compliance team collaboration empowers you to deliver quick and valuable data analytics on the most sensitive data to unlock the full potential of your cloud data platforms. Learn how we streamline and accelerate manual processes to help you derive real results from your data at dataengineeringpodcast.com/immuta. Today’s episode of the Data Engineering Podcast is sponsored by Datadog, a SaaS-based monitoring and analytics platform for cloud-scale infrastructure, applications, logs, and more. Datadog uses machine-learning based algorithms to detect errors and anomalies across your entire stack—which reduces the time it takes to detect and address outages and helps promote collaboration between Data Engineering, Operations, and the rest of the company. Go to dataengineeringpodcast.com/datadog today to start your free 14 day trial. If you start a trial and install Datadog’s agent, Datadog will send you a free T-shirt. Your host is Tobias Macey and today I’m interviewing Jesse Anderson about best practices for organizing and managing data teams

Interview

Introduction How did you get involved in the area of data management? Can you start by giving an overview of how you view the mission and responsibilities of a data team?

What are the critical elements of a successful data team? Beyond the core pillars of data science, data engineering, and operations, what other specialized roles do you find hel

What you must know to protect yourself today The digital technology explosion has blown everything to bits--and the blast has provided new challenges and opportunities. This second edition of Blown to Bits delivers the knowledge you need to take greater control of your information environment and thrive in a world thats coming whether you like it or not. Straight from internationally respected Harvard/MIT experts, this plain-English bestseller has been fully revised for the latest controversies over social media, fake news, big data, cyberthreats, privacy, artificial intelligence and machine learning, self-driving cars, the Internet of Things, and much more. Discover who owns all that data about youand what they can infer from it Learn to challenge algorithmic decisions See how close you can get to sending truly secure messages Decide whether you really want always-on cameras and microphones Explore the realities of Internet free speech Protect yourself against out-of-control technologies (and the powerful organizations that wield them) You will find clear explanations, practical examples, and real insight into what digital tech means to you--as an individual, and as a citizen.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted 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 Notes 5:39 – Paul’s experience  9:07 – Paul’s new book 12:00 – 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 tips 31:30 – Twitter comment Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  The AI Ladder Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Hosted 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 [[email protected]] 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 Notes

1. https://www.ibm.com/blogs/watson-health/author/kyurhee/
2. https://www.ibm.com/impact/covid-19/

Connect with the Team

Producer Kate Brown - LinkedIn.

Producer Michael Sestak - LinkedIn. Producer Meighann Helene - LinkedIn.

Host Al Martin - LinkedIn and Twitter.

Additional resources:   IBM Watson Health COVID-19 Resources: https://www.ibm.com/watson-health/covid-19

IBM Watson Health: Micromedex with Watson: https://www.ibm.com/products/dynamed-and-micromedex-with-watson

How governments are rising to the challenge of COVID-19: https://www.ibm.com/blogs/watson-health/governments-agencies-rising-challenge-of-covid-19/

Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

A revolution is occurring in data management regarding how data is collected, stored, processed, governed, managed, and provided to decision makers. The data lake is a popular approach that harnesses the power of big data and marries it with the agility of self-service. With this report, IT executives and data architects will focus on the technical aspects of building a data lake for your organization. Alex Gorelik from Facebook explains the requirements for building a successful data lake that business users can easily access whenever they have a need. You'll learn the phases of data lake maturity, common mistakes that lead to data swamps, and the importance of aligning data with your company's business strategy and gaining executive sponsorship. You'll explore: The ingredients of modern data lakes, such as the use of different ingestion methods for different data formats, and the importance of the three Vs: volume, variety, and velocity Building blocks of successful data lakes, including data ingestion, integration, persistence, data governance, and business intelligence and self-service analytics State-of-the-art data lake architectures offered by Amazon Web Services, Microsoft Azure, and Google Cloud

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted 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 Notes 1:37 – Nancy’s bio 3:10 - Are we talking Money Ball? 5:52 - On Base percentage 7:08 – Analyse examples  10:02 – Do you control the data? 11:24 – Out there statistics 14:12 - Can analytics go to far? 17:35 – Real time analysis 18:45 – Covid and sports 21:15 – Your role in sports betting 22:50 – What’s the most fascinating thing you’ve learned? 25:23 – What’s the future?

Website - Stats Perform Money Ball Stats Perform - Twitter  Bill James – Baseball Abstract  The Analyst     Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Manipulating and processing masses of digital data is never a purely technical activity. It requires an interpretative and exploratory outlook – already well known in the social sciences and the humanities – to convey intelligible results from data analysis algorithms and create new knowledge. Big Data is based on an inquiry of several years within Proxem, a software publisher specializing in big data processing. The book examines how data scientists explore, interpret and visualize our digital traces to make sense of them, and to produce new knowledge. Grounded in epistemology and science and technology studies, Big Data offers a reflection on data in general, and on how they help us to better understand reality and decide on our daily actions.