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 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 Notes
6:30 – What is a data framework?
9:16 – What is framework?
11:00 – Governance and people
14:15 – Process and architecture
19:15 – Bringing it all into a playbook
22:56 – Who is the client?
24:36 – How does bias play into it?
27:02 – What products are you using?
27:54 – Explainability
30:44 – Ethics of AI
37:13 Suj and Richard’s most important lessons in AI
The Discipline of Technology
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
[Replay] Al and Lynne Snead discuss leadership, coaching and being your best self and mixing that in with data
[Replay] Understanding Apache Spark with Jean-Georges Perrin
This week Al and Elo Umeh discuss Terragon, how it benefits the businesses in Africa
This week Al and Anastasia Leng discuss infusing creative with data
[Part 2] Al, Trent Gray-Donald, and Dakshi Agrawal discuss the technology around hybrid cloud data fabric, IBM Watson, and leadership
[Part 1] Al, Trent Gray-Donald, and Dakshi Agrawal discuss the technology around hybrid cloud data fabric, IBM Watson, and leadership
Al and Alex Watson discuss Gretel, security, and privacy issues around synthetic data
[Replay] Optimizing Sports using A.I. with Joe Pavitt
[Part2] Al and Neil discuss why data is wrong, how you fix it, and Neil’s book.
[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
Al and Davor Bonaci discuss how feature stores save time and money in production systems and then leadership of a startup company
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
Al and Matt Cowell discuss defining data literacy, teaching products, and learning problems
[Part2] Al and Kordel France discuss helping medical professions save lives and how did Kordel get into the medical field
[Part1] Al and Kordel France discuss helping medical professions save lives and how did Kordel get into the medical field
[Replay] Al, Dale, and Hai-Nhu discuss the IBM initiative to modernize IT language to remove racial and cultural bias (aka Words Matter)
Al and Lillian Pierson discuss Data Mania and Lillian’s book Data Science For Dummies
Al and Milan Shetti discuss Z and what it means when we say legacy powers legendary
[Replay] Al and Nancy Hensley discuss Data and AI and its impact on sports
Create your
podcast in
minutes
It is Free