Any data scientist knows that Big Data success is all about features, features, features. Feature engineering rules!
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Industry Perspectives
A Laundry List for Cleaning Messy Data and Making It Business Ready
In this special guest feature, Mark Palmer, TIBCO SVP & GM of Analytics, Data Science & Data Virtualization, believes that companies who learn to leverage their data will beat out their competition. Making data-driven decisions for business strategy is essential in today’s tech-centric environment, and anyone who is not taking advantage of the information they’ve gathered will fall behind.
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Interview: Global Technology Leader PNY
The following whitepaper download is a reprint of the recent interview with our friends over at PNY to discuss a variety of topics affecting data scientists conducting work on big data problem domains including how “Big Data” is becoming increasingly accessible with big clusters with disk-based databases, small clusters with in-memory data, single systems with in-CPU-memory data, and single systems with in-GPU-memory data. Answering our inquiries were: Bojan Tunguz, Senior System Software Engineer, NVIDIA and Carl Flygare, NVIDIA Quadro Product Marketing Manager, PNY.
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