Making Data Simple show

Making Data Simple

Summary: Hosted by Al Martin, WW VP Account Technology Leaders at IBM. Making Data Simple provides the latest thinking on leadership, big data, A.I., and the implications for the enterprise from a range of experts.

Join Now to Subscribe to this Podcast

Podcasts:

 This week Al and Davit Buniatyan discuss reconstruction of the connectome of a mouse's brain, research in machine learning, and managing unstructured data | File Type: audio/mpeg | Duration: 2604

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 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 Davit Buniatyan. Davit is founding CEO of Activeloop, he started his PhD at Princeton University, his research involved reconstructing the connectome of the mouse brain. In this research he dealt with large-scale unstructured data which was extremely expensive (amounting to millions of dollars) to manage. Later on, he realized that this problem is a real pain point, not only in the lab setting but also for many companies across industries. This made him think of a radically more efficient, and a machine-learning native way to work with data. The idea of changing how an ML team can create and manage datasets got him into Y Combinator, where he started Activeloop, a startup that has attracted the investment of prominent Silicon Valley VC firms and angel investors, and the attention of the open-source community, with the framework trending number 1 in Python on GitHub worldwide earlier this year. Show Notes 2:05 – Davit’s experience 6:44 – What is your success criteria in the mouse connectome? 8:44 – What did you learn from this? 10:00 – Could this solve ALS? 13:19 – What is the problem you’re solving 17:17 – How do you prepare the data? 24:00 – Why are the naysayers wrong? 25:21 – What is the name of the technology? 31:19 – What problem have you not solved? 37:44 – What keeps you up at night? 38:42 – How are you finding talent?  41:06 – What do you do for fun? Activeloop Activeloop - Twitter Davit Buniatyan - LinkedIn Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 Al and Mark Gabrielson discuss RegTech, Safer Payments, and OpenPages and how they can control your governance and compliance policies | File Type: audio/mpeg | Duration: 2162

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 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 Mark Gabrielson leads RegTech in Expert Labs which is a division of Services that is associated with Development. Mark joined IBM via the Informix acquisition. In the last 10 years Mark has been leading IBMs Commercial Payments Practice. Mark is currently working on projects involving Safer Payments and OpenPages. Show Notes 4:50 – What’s your most favorite job? 7:58 – Describe RegTech  13:19 – Breaking down silos 20:56 – How do you do it with AI? 23:05 – What is OpenPages sweet spot? 26:50 – If I am a client how do I get started? 30:28 – Who are the competitors? Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 [Replay] Al and Lynne Snead discuss leadership, coaching and being your best self and mixing that in with data | File Type: audio/mpeg | Duration: 1717

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 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 background 5:40 – Lynne’s coaching specialty and mission statement 10:30 – Why don’t all leaders have coaches? 12:08 – Why do you differentiate corporate coaching from life coaching? 16:27 - Do you believe in the element of natural state?  18:32 – How many individuals have you coached? 19:49 – What constitutes a great leader? 20:55 – What are the common mistakes in a leader? 24:44 – Steer them back on track Lynne Snead - LinkedIn Talent Evolution Systems Lynne’s email: lsnead@talentevolutionsystems.com Leadership and self deception  How will you measure your life? Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 [Replay] Understanding Apache Spark with Jean-Georges Perrin | File Type: audio/mpeg | Duration: 1776

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 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 Jean-Georges Perrin, Director of Engineering at weexperience. Together, they discuss — and compare — Apache Spark and Hadoop, and explain what it means to hold the title of IBM Champion. Show Notes 02:07 - Connect with Jean-Georges Perrin on LinkedIn and Twitter, and check out his website. 13:14 - Check out Jean-Georges' book on Apache Spark. 24:38 - What does it mean to be an IBM Champion? Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 This week Al and Elo Umeh discuss Terragon, how it benefits the businesses in Africa | File Type: audio/mpeg | Duration: 2266

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 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 Elo Umeh, from Terragon Africa’s fastest-growing enterprise marketing technology company. Terragon uses its on-demand marketing cloud platform, attribution software, and deep analytics capability to enable thoughtful, targeted omni-channel access to 100m+ mobile-first African consumers. Elo is the Founder and CEO at Terragon Group. Elo career has spanned over 15 years where he has worked in the mobile and digital media across East and West Africa. He was part of the founding team at Mtech Communications. Elo holds a global executive MBA from IESE business of school where he graduated at the top of his class. Elo also has a Bachelor’s degree in Business Administration from Lagos State University. Show Notes 4:02 – What keeps you going? 6:15 – Lets dive into Terragon 8:40 – Who are your customers? 11:06 – Define pre-paid 14:40 – What kind of incites and security are you providing? 20:37- What kind of technology is Terragon using? 23:16 – What was it about the smart phone that made you want to go out on your own? 26:10 – Who’s your biggest competitor?  28:20 – What’s next for Terragon? 31:01 – What are the biggest mistakes entrepreneurs make? Terragon  Elo Umeh - LinkedIn  Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 This week Al and Anastasia Leng discuss infusing creative with data | File Type: audio/mpeg | Duration: 2705

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 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 Anastasia Leng is CEO and Founder of Creative X. Anastasia previously worked at Google, in 2012 Anastasia started an e-Commerce business which then lead to Creative X.  Show Notes 4:13 – How much time do you spend on funding? 7:08 – Why do it again? 13:28 –Is this the ending days of Hatch or the early days of Creative X? 18:00 – How would you label your business? 23:38 – What technology are you using? 27:21 – Who is your target customer? 34:14 – Are there other competitors doing this today? 36:34 – Customer stories 38:38 – Are you using AI? Email - anastasia@creativex.com Anastasia - LinkedIn  Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 [Part 2] Al, Trent Gray-Donald, and Dakshi Agrawal discuss the technology around hybrid cloud data fabric, IBM Watson, and leadership | File Type: audio/mpeg | Duration: 1834

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 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 Trent Gray-Donald Distinguished Engineer, IBM Data and AI, Dakshi Agrawal IBM Fellow and CTO, IBM AI.  Trent Gray-Donald spend his first 16 years on manage language runtime, then moved over to Data and AI, and then Cloud Pak for Data.  Dakshi Agrawal joined IBM right after his Phd in IBM Research, then Dakshi moved into software development, and in the 6 years in AI.  Show Notes .15 - 5:23 - Repeat of introductions from Part 1 5:50 – What is AI Anywhere? 9:09 – Does it make our development more difficult? 11:22 – Does data virtualization work? 15:31 - How do we get started with AI? 17:41 – Customer success stories Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 [Part 1] Al, Trent Gray-Donald, and Dakshi Agrawal discuss the technology around hybrid cloud data fabric, IBM Watson, and leadership | File Type: audio/mpeg | Duration: 1484

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 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 Trent Gray-Donald Distinguished Engineer, IBM Data and AI, Dakshi Agrawal IBM Fellow and CTO, IBM AI.  Trent Gray-Donald spend his first 16 years on manage language runtime, then moved over to Data and AI, and then Cloud Pak for Data.  Dakshi Agrawal joined IBM right after his Phd in IBM Research, then Dakshi moved into software development, and in the 6 years in AI.  Show Notes 5:24 – Why is IBM Watson important? 10:28 – How does data fabric fit in? 15:25 – How would you describe the customer journey around data fabric? 17:10 – Is the ultimate destination AI? Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 Al and Alex Watson discuss Gretel, security, and privacy issues around synthetic data | File Type: audio/mpeg | Duration: 2639

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 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 Alex Watson. Alex was previously a GM at AWS and is currently a Co-Founder at Gretel.ai. Gretel is a privacy startup that enables developers, researchers, and scientists to quickly create safe versions of data for use in pre-production environments and machine learning workloads, which are shareable across teams and organizations. These tools address head-on the massive data privacy bottleneck--which has stifled innovation across multiple industries for years—by equipping builders everywhere with the ability to create quality datasets that scale. In short, synthetic data levels the playing field for everyone. This democratization of data will foster competition, scientific discoveries, and the inventions that will drive the next revolution of our data economy.  The company recently closed their series-A funding, led by Greylock, for another $12 million and brought Jason Warner, the current CTO for GitHub, on as an investor. Gretel also launched its latest public beta, Beta2, which offers privacy engineering as a service for everyone, not just developers. Show Notes 2:03 – Alex’s background 4:36 – What time frame was Harvest AI? 7:14 – How does NLP play into Harvest AI? 10:50 – How can we not have enough knowledge? 14:08 – Does the tech exist today for security? 18:14 – Privacy issues 20:42 – What does Gretel stand for? 27:42 – Do you increase the opportunity for bias? 31:18 – Where is the sweet spot for Gretel? 33:30 – When do synthetic not work? 37:42 – What is practical privacy? Gretel Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 [Replay] Optimizing Sports using A.I. with Joe Pavitt | File Type: audio/mpeg | Duration: 1996

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, our guest is Joe Pavitt, master inventor and emerging technology specialist at IBM. Joe comes from a diverse background of playing various sports at a high-level, while pursuing studies in engineering and technology. Tune in to discover how Joe's role allows him to be at the intersection of these 2 seemingly opposed industries. Connect with Joe LinkedIn Show Notes 05:29 - Check out this article on the effects of alcohol on athletic performance.  07:00 - IBM has spent the last 25 years at the top spot for patents created.   12:29 - Watch this video to learn more about what Joe is doing with Leatherhead F.C. 25:56 - Learn more about the Blender project and animation on their website.   Connect with the Team Producer Liam Seston - LinkedIn. Producer Lana Cosic - LinkedIn. Producer Meighann Helene - LinkedIn.  Host Al Martin - LinkedIn and Twitter. Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. 

 [Part2] Al and Neil discuss why data is wrong, how you fix it, and Neil’s book. | File Type: audio/mpeg | Duration: 1739

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 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 Neil Gilbert Siegel. Neil has lead the creation of a large number of successful military intelligence and commercial systems, this includes the US Blue Force tracker, Neil, has had a number of advances in consumer electronics and health care, a number of patents. Neil also has a number of wards including the US National Academy of Engineering and a Fellow of the National Academy of Inventors. And finally an author of Engineering Project Management.    Show Notes 2:49 – Why is all data wrong? 9:00 – How do you fix wrong data? 23:17 – Where did you get your love for engineering? Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Nassim Nicholas Taleb – Fooled by Randomness - Black Swan Engineering Project Management NeilSiegel.usc.edu

 [Part1] Al and Neil Gilbert Siegel discuss Neil’s involvement with the US Military, his inventions, Neil’s book and tune into part 2 to find out about Neil’s family | File Type: audio/mpeg | Duration: 1662

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 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 Neil Gilbert Siegel. Neil has lead the creation of a large number of successful military intelligence and commercial systems, this includes the US Blue Force tracker, Neil, has had a number of advances in consumer electronics and health care, a number of patents. Neil also has a number of wards including the US National Academy of Engineering and a Fellow of the National Academy of Inventors. And finally an author of Engineering Project Management.     Show Notes 2:20 – Tell us about IBM 3:03 – How do you describe yourself? 8:37 – Can you talk about the first US Army unmanned aerial vehicle? 11:13 – Can you give us some examples of the smartphone and tablet components? 18:30 – What’s your favorite invention?  20:20 – Why a book about Engineering and Management?  Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 Al and Davor Bonaci discuss how feature stores save time and money in production systems and then leadership of a startup company | File Type: audio/mpeg | Duration: 2347

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 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 Davor Bonaci co-founder and CEO of a Seattle-based startup Kaskada. Previously, Davor served as the chair of the Apache Beam PMC and software engineer in Google Cloud since its early days and the inception of Cloud Dataflow. Show Notes 2:39 – Are you focused on the platform or the models around event based data? 6:52 – Does your company provide knowhow or is it tooling? 9:58 – What’s your secret sauce? 11:19 – How did you end up here? 15:40 – Who’s your biggest competitor?  17:13 – Can you talk to some of the common use cases? 20:30 – Are you and IDE, how does it work? 21:18 – Are you a subscription service? 22:18 – What’s your 5 year plan? 26:44 – How feature store save time and money 29:19 – Describe the company in three bullets 31:35 – What are the top skills?  Davor Bonaci  - LinkedIn Kaskada Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 Al and Wendy Gonzalez discuss data is the new code, micro models that are reuseable, data pipeline and hiring people that are smarter than you | File Type: audio/mpeg | Duration: 2700

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 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 Wendy Gonzalez, Wendy is an executive that is passionate about building high-performing, high-functioning teams that develop and scale innovative, impactful technology. Wendy has two decades of managerial and technology leadership experience for companies including EY, Capgemini, Cycle30 (acquired by Arrow Electronics) and General Communications Inc. Wendy is an active Board Member of the Leila Janah Foundation. Show Notes 2:39 – How does a CEO run a company from home? 4:50 - Outline the Mission Statement 7:00 – How do you hire people? 8:58 – How big is the company? 9:23 – What’s your secret sauce? 12:10 – How does this tie back to social? 18:38 – Can you talk more about your statistics? 20:55 – How do you separate your business from others? 24:22 – Are these micro models reusable? 25:59 – What is a typically engagement look like? 29:30 - How do clients find you? 30:38 – How did Sama get started? Turing the flywheel Omnivore’s Delemma Sama  Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

 Al and Matt Cowell discuss defining data literacy, teaching products, and learning problems | File Type: audio/mpeg | Duration: 2770

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 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 Matt Cowell. Matt serves as CEO at QuantHub, a leading data upskilling and assessment platform that helps companies create a data literate workforce across the entire enterprise. Matt uses his wealth of experience as a product and tech executive to forge the company strategy to address one of the most significant corporate challenges of the 2020’s, the data skill gap. Prior to QuantHub, Matt spent 15 years running product and tech at PE-backed companies, including building a product and engineering organization at Daxko - delivering 10x revenue growth, 7 acquisitions, and 3 enormously successful recapitalization. While at Daxko, Matt led the team to deliver the first machine learning/AI solution to the gym/fitness market. Matt is passionate about facilitating the data fluency of individuals and organizations all over the world and loves focusing on the people side of the equation. Show Notes 2:25 – How do you go from SVP of Products to getting into the data learning business? 3:48 - How do you define data literacy?  5:50 – Do you teach the products? 7:36 - What’s out of scope? 12:50 – Client use case 18:07 – Solving learning problems 21:14 – What does a learning plan look like? 25:08 – Define Micro 30:20 – What’s the best way to learn? 33:14 – How do you measure success? 34:47 - Are you venture capital funded? 36:10 – Do you have a fundamental leadership belief? 38:24 – What skill do you value most in a leader?    QuantHub Upskill quanthub Monetizing innovation  Ultra Learning Matt Cowell - LinkedIn Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

Comments

Login or signup comment.