Podcasts

Making Data Simple: What's next in the world of data and analytics with Seth Dobrin, Part 2

Making Data Simple: What's next in the world of data and analytics with Seth Dobrin, part 2

January 24, 2018 | 21:19
In this episode of the Making Data Simple Podcast, Seth Dobrin, vice president and chief data officer for IBM Analytics, and Al Martin continue their conversation about data in 2018. Find out the six steps to make your enterprise data driven, how machine learning and AI will impact your business...
Making Data Simple: What's next in the world of data & analytics with Seth Dobrin, part 1

Making Data Simple: What's next in the world of data & analytics with Seth Dobrin, part 1

January 18, 2018 | 27:47
What's next in the world of data and analytics in 2018? In part one of Al Martin's discussion with Seth Dobrin, Vice President and Chief Data Officer for IBM Analytics, explore the strategies and people your company needs to disrupt and succeed in the year ahead. Do you or your team members need...
Making Data Simple: Cloud computing, part 1

Making Data Simple: Cloud computing, part 1

December 14, 2017 | 21:48
Do you know how often you are using the cloud every single day? In part one of our discussion with IBM Fellow Sam Lightstone, learn about cloud computing and why it is increasingly important in our data-driven world. Also, learn alternatives to loading private data to the cloud, data movement, and...
Making data simple: Data movement at size and scale

Making Data Simple: Data movement at size and scale

December 6, 2017 | 27:29
Michael Springgay, IBM STSM, Db2 Data Warehouse Development, and Rajani Maindiratta, IBM Senior Manager, Db2 Data Warehouse on Cloud Development for Load, share their experiences moving data for customers big and small. What are the options for data movement and what is the impact of cloud?
Making Data Simple: The 5 areas businesses MUST get right

Making Data Simple: The 5 areas businesses MUST get right

November 13, 2017 | 27:13
What is driving change in the world of data? In his keynote from the Big Data Summit KC 2017, our Making Data Simple podcast host and IBM Analytics VP Al Martin addresses disruption, the data maturity model and the five areas business must get right to succeed in the era of cognitive computing.
Making Data Simple: Growth Hacking - Not just for start ups

Making Data Simple: Growth hacking - not just for start ups

October 18, 2017 | 26:32
How did companies like Facebook and Airbnb get so big so fast? What can we learn from them? Why is data so important for growth? Nancy Hensley, Director of Strategy & Growth for IBM Hybrid Cloud, has the answers in this episode of Making Data Simple.
Making Data Simple: Will machines take our jobs?

Making Data Simple: Will machines take our jobs?

October 10, 2017 | 41:59
In this episode of Making Data Simple we hear insights from IBM Machine Learning Hub data scientists Jorge A. Castañón and Óscar Lara-Yejas as they discuss what machine learning is and is not. They also answer the most controversial question today: Will machines take our jobs? Come find out!
Making Data Simple: A new definition of client care

Making Data Simple: A new definition of client care

October 5, 2017 | 38:24
How do you provide answers to clients prior to them asking? What do you do with an abundance of client data? In this episode of Making Data Simple, Tracy Bolot, Director of Digital Client Support for Analytics at IBM, talks about how to maximize teamwork and strengths to enrich your clients'...
Making Data Simple: End of tech companies

Making Data Simple: End of tech companies

September 27, 2017 | 27:23
In this episode of Making Data Simple, we welcome Rob Thomas, GM of IBM Analytics, who shares his insights on turning data into insights.
Making Data Simple: The big data problem

Making Data Simple: The big data problem

September 20, 2017 | 25:49
In this first episode of Making Data Simple, we welcome Daniel Hernandez, VP of IBM Analytics Offering Management, who helps us navigate "the big data problem" and shares why he doesn't like the term "big data."

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