Top 10 IBM Big Data & Analytics Hub podcasts of 2017

Social Media Execution Strategist, IBM

It can be difficult to keep up with all the best podcast episodes during the year. That's why we've compiled the Top 10 podcasts of the year from the IBM Big Data & Analytics Hub Insights Podcast feed right here. These are the episodes that resonated most with Hub readers around popular topics such as cognitive analytics, machine learning and growth hacking, to name a few. So sit back in your comfy chair around the fire (or simulated fire on your monitor) and take a few minutes to explore something new.

10. In the age of data: Killer data, part 1

A two part discussion about Chunka Mui’s book, The New Killer Apps: How Large Companies Can Out-Innovate Start-Ups.

9. Machine learning in hybrid transaction/analytics processing

IBM Distinguished Engineer Jeff Josten discusses how the value of machine learning in enterprise applications of hybrid transaction/analytics processing.

8. Making Data Simple: The 5 areas businesses MUST get right

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. 

7. Making Data Simple: End of tech companies

Rob Thomas, general manager of analytics at IBM, discusses data, tech companies and his two books, Big Data Revolution and The End of Tech Companies.

6. Making Data Simple: The big data problem

In this inaugural episode of Making Data Simple, host Al Martin welcomes Daniel Hernandez, vice president of IBM Analytics Offering Management, who discusses "the big data problem" and shares why he doesn't like the term "big data."

5. Making Data Simple: Growth hacking - not just for startups 

Nancy Hensley, director of strategy and growth for IBM Hybrid Cloud discusses how to use growth hacking strategies to build your business and why growth hacking isn't just for startups.

4. Why is prescriptive analytics essential for businesses?

Ferenc Katai, offering manager for IBM ILOG CPLEX Optimization Studio, share his thoughts on why prescriptive analytics is essential for businesses.

3. Machine learning in the evolution of data science

Steven Astorino, vice president of development for IBM Private Cloud Analytics Platform discusses how machine learning is driving the evolution of data science in strategic business initiatives.

2. Machine learning in cognitive analytics

Dinesh Nirmal, vice president, IBM Analytics Platform Development, discusses the role that machine learning plays in enterprise cognitive analytics initiatives. 

1. Data science for real-time streaming analytics

Roger Rea, senior offering manager for IBM Streams, shares his thoughts on how data scientists can create real-time applications using IBM Streams.

If you'd like to hear all the latest from the Big Data and Analytics Hub, you can find our entire catalog of past episodes right here or subscribe on iTunes, Google Play Music, or wherever you get your podcasts. Happy listening.