Rob Thomas & Joel Horwitz, IBM - #BigDataNYC 2015 - #theCUBE
Channel: SiliconANGLE theCUBE
Date: 2015-09-29

01. Rob Thomas, IBM, Visits #theCUBE. (00:22)
02. Joel Horwitz, IBM, Visits #theCUBE. (00:44)
03. Big Data Maturity Curve. (00:50)
04. Hadoop Is Becoming More of a Storage Environment. (02:45)
05. Does Scale Up or Scale Out Really Matter. (04:45)
06. Datapalooza:  Three Day Training Event. (06:43)
07. New Products:  Big Integrate and Big Quality. (09:06)
08. Differentiating from the Competition. (10:58)
09. Making Strong Investments in the Open Source Community. (11:51)
10. IBM Cloud Data Services. (13:44)
11. Reaching New Communities. (17:16)
12. Myth:  All Machine Learning Is Created Equal. (19:43)
13. Myth:  Adoption of New Technologies. (21:00)
14. Upcoming Events:  Datapalooza and Spark Summit. (22:04)
15. Spark Has Been Built Like a Stand Alone Company. (22:40)

Track List created with http://www.vinjavideo.com.
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Big Data trends: Outcomes not architecture | #BigDataNYC
by Marlene Den Bleyker | Sep 29, 2015 

As Big Data hits the Big Apple, industry insiders are beginning to see big shifts in customer requirements for their data. What are the current trends?

Rob Thomas, vice president of product development, analytics for IBM, and Joel Horwitz, director of marketing analytics for IBM, sat down with John Furrier, host of theCUBE, from the SiliconANGLE Media team, during BigData NYC 2015 to discuss the customer trends they are seeing in the industry.

A maturity curve

Thomas explained that Big Data has a maturity curve. He has seen a major change over the past five years. He said, “When I talked to clients in the past, it was about storage and extending the warehouse. Now it’s about line of business conversations, analytics, applications and how to build business models around data.”

When asked about trends in how companies are scaling their systems, Thomas noted that the huge trend is diversity. He said that from a customer perspective the value comes from machine learning. “Scale up or scale out is interesting for the guy running the cloud environment, but it doesn’t change the outcome or the insight a client is getting.”

Delivering analytics

For the team at IBM, the discussion has shifted to outcomes not architecture. The goal is to make it easy for the customer to gather and evaluate analytics.

Horwitz and Thomas both have strong feelings about what Hadoop is and is not. According to Horwitz, “Hadoop is becoming a storage environment.” He believes that Spark is accelerating Hadoop and making analytics easier to capture.

Misguided or myth

Commenting on some misguided concepts and myths in the industry, the pair had some interesting takeaways. Horwitz stated, “All machine learning is not created equal.” He suggested that there are different levels out there right now and he feels that there is a need for an industry standard.

Thomas feels that the adoption of new technology is not happening as fast as people think. Indicating that there are gaps in skill levels, he said, “Most enterprises have IT skills, but they need data science skills. Until they close that gap, adoption will not be as fast.”

@theCUBE
#BigDataNYC