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February 2017, Vol. 5, No. 1

Streaming data analytics puts real-time pressure on project teams

When I worked at a fast-food restaurant in high school, a co-worker friend and I decided its motto should be "Speed, Not Perfection." We silkscreened t-shirts for the two of us with that phrase embedded in the corporate logo -- two smart-aleck teenagers gently sticking it to the man. Nowadays, data management and analytics teams increasingly find themselves being asked to fulfill the speed part to enable real-time data analysis in their organizations. But they don't have the luxury of being able to get by with the same sort of occasional sloppiness that my friend and I did in slapping burgers together. And that puts them under a lot of pressure, because creating a real-time architecture and using it to run streaming data analytics applications is a complicated undertaking. For starters, streaming analytics systems don't come in a box -- not even a large one. Setting them up is an artisanal process that requires prospective users to piece together various data processing technologies and analytics tools to meet their particular ...

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