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Don’t leave data behind: Spark as a translator for data | #SparkSummit
What makes Apache Spark so unique? There are many reasons it is seen as such an innovative platform, according to Joel Horwitz, director of Corporate and Business Development at IBM Analytics. Instead of trying to be “the one notebook to rule them all,” IBM focused on figuring out what makes data scientists tick and what they’re specifically looking for, through hundreds of interviews, Horwitz explained.
“Spark is a translator for working with all kinds of data,” said Horwitz, who spoke to John Walls and Peter Burris (@plburris), cohosts of theCUBE, from the SiliconANGLE Media team, during Spark Summit 2016. It has all the needed ingredients and the core components to make it useful and portable. Without that portability aspect, it’s easy to leave data behind.
Strategic opportunity
Burris pointed out that IBM has always walked the line between following and innovating, and one of the ROIs is their relationship with Spark. It also serves as proof of commitment.
“We see this as a strategic opportunity,” said Horwitz. IBM was the first through the door in recognizing the value of Spark, and it was willing to disrupt its old way of doing things. Spark is now being used across IBM, and the ROI isn’t just incremental – it’s about bringing products to the market more quickly.
Looking toward the future, Walls asked what would be considered a benchmark activity should they meet again next year in 2017. To Horwitz, the most important thing is community. In the future, he hopes to see more people rallying around Spark as an operating system.
Watch the full interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of Spark Summit 2016.
Photo by SiliconANGLE
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