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56 SMT Magazine • November 2015 by Chandran Nair NATioNAl iNSTruMeNTS There once was a time when hardware sam- pling rates, limited by the speed at which ana- log-to-digital conversion took place, physically restricted how much data was acquired. But the advances in computing technology, including increasing microprocessor speed and hard-drive storage capacity, combined with decreasing costs for hardware and software, have provoked an explosion of data coming in unabated. Among the most interesting to the engineer and scien- tist is data derived from the physical world. This is analog data that is captured and digitized and otherwise known as "big analog Ddata." It is collected from measurements of vibration, RF signals, temperature, pressure, sound, image, light, magnetism, voltage, and so on. In the field of measurement applications, engineers and scientists collect vast amounts of data every minute. For every second that the Large Hadron Collider at the European Orga- nization for Nuclear Research (CERN) runs an experiment, the instrument generates 40TB of data. For every 30 minutes that a Boeing jet en- gine runs, the system creates 10TB of operations information (Gantz, 2011). In the age of big data, hardware is evidently no longer the limiting factor in acquisition ap- plications, buy the management of acquired data is. How do we store and make sense of data? How do we keep them secured? How do we future proof them? These questions become compounded when systems evolve to become more complex, and the amount of data re- quired to describe those systems grow beyond comprehension. This inevitably results in lon- ger project schedules and less efficiency in de- velopment. More advanced tools and smarter measurement systems will be essential to man- aging this explosion of data and help engineers make informed decisions faster. For engineers, this means instrumentation must be smarter and sensors, measurement hardware, data buses, and application soft- ware need to work together to provide action- able data at the right time. The big data phe- FeaTure

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