01. Joel Horowitz, IBM, visits theCUBE !. (00:19)
02. The Evolution of the Spark Community Relative to Hadoop. (01:20)
03. The IBM Investment in Spark. (04:03)
04. The Work that IBM Layered on Linux. (05:40)
05. The Development of Spark and Spark's Portability. (08:010)
06. The Bigfoot Trap. (11:12)
07. Spark's Repeatable Architectures. (12:52)
08. Moving Data Science into the Marketplace. (16:20)
09. Engineering and Data Science as a Team Sport. (17:42)
#theCUBE #IBM #SparkSummitEast #SparkSummit #Spark #SiliconANGLE
--- ---
Data scientists vs. data engineers: Data science is a team sport at IBM | #SparkSummit
by Marlene Den Bleyker | Feb 18, 2016
IBM is investing heavily in Spark during its early days. This investment eclipses monetary value by actually incorporating Spark into its analytics platforms and cloud offerings along with growing the community to add usability, features and functions for the enterprise.
Early days of Spark
Joel Horwitz, director of corporate and business development, Analytics at IBM stopped by to talk with Jeff Frick and George Gilbert, cohosts of theCUBE, from the SiliconANGLE Media team, during Spark Summit East 2016 in New York City, to talk about IBM’s different approach to using Spark.
“It’s early days for Spark, and that is partly why we opened up the Spark Technology Center, partly to help bring a business solution oriented thinking to the Spark community. I think that’s what IBM brings to the table,” said Horwitz, who noted there is still a great deal of work to do.
Horwitz explaineds that IBM took a very different approach with Spark by growing the community contributing to spark and consuming it with a number of the company’s solutions.
Data science is a team sport
When asked about data scientist versus data engineers, Horwitz said, “You can’t do data science without data engineers. It’s a team sport – be careful to not individualize it. It’s a whole field.”
@theCUBE
#SparkSummit
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Joel Horwitz, IBM | Spark Summit East 2016
01. Joel Horowitz, IBM, visits theCUBE !. (00:19)
02. The Evolution of the Spark Community Relative to Hadoop. (01:20)
03. The IBM Investment in Spark. (04:03)
04. The Work that IBM Layered on Linux. (05:40)
05. The Development of Spark and Spark's Portability. (08:010)
06. The Bigfoot Trap. (11:12)
07. Spark's Repeatable Architectures. (12:52)
08. Moving Data Science into the Marketplace. (16:20)
09. Engineering and Data Science as a Team Sport. (17:42)
#theCUBE #IBM #SparkSummitEast #SparkSummit #Spark #SiliconANGLE
--- ---
Data scientists vs. data engineers: Data science is a team sport at IBM | #SparkSummit
by Marlene Den Bleyker | Feb 18, 2016
IBM is investing heavily in Spark during its early days. This investment eclipses monetary value by actually incorporating Spark into its analytics platforms and cloud offerings along with growing the community to add usability, features and functions for the enterprise.
Early days of Spark
Joel Horwitz, director of corporate and business development, Analytics at IBM stopped by to talk with Jeff Frick and George Gilbert, cohosts of theCUBE, from the SiliconANGLE Media team, during Spark Summit East 2016 in New York City, to talk about IBM’s different approach to using Spark.
“It’s early days for Spark, and that is partly why we opened up the Spark Technology Center, partly to help bring a business solution oriented thinking to the Spark community. I think that’s what IBM brings to the table,” said Horwitz, who noted there is still a great deal of work to do.
Horwitz explaineds that IBM took a very different approach with Spark by growing the community contributing to spark and consuming it with a number of the company’s solutions.
Data science is a team sport
When asked about data scientist versus data engineers, Horwitz said, “You can’t do data science without data engineers. It’s a team sport – be careful to not individualize it. It’s a whole field.”
@theCUBE
#SparkSummit
