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DATA AND SIGNAL PROCESSING FOR BUSINESS

Data is the new god, raised by our times. Some call it “Big Data” and there are persons afraid it is a crueler sibling of “Big Brother”. The source of the huge amounts of data is not given any more by sophisticated scientific experiments or by searches in the Universe, but generated by our very existence. Many of them regard economic or social resources and the quantity of data exceeds Terabytes or Petabytes, making its processing a tedious and challenging undertaking.

That is where standard techniques of data and signal processing can make their importance known. Methods like sampling, filtering, Fourier Transform and Principal Component Analysis apply to large data collections to extract important features or to prepare it for further processing.

Signal Processing can be seen as domain of engineering (electrical and electronic) that models and analyzes the quantitative representations of physical events. The inputs are usually electric signals, but the methodologies are not restricted to them and are proven for decades, resulting in a comprehensive and proven experience. The paper describes the practice in giving the Data and Signal Processing for Business subject at the Master program in Business Administration and Engineering from University POLITEHNICA of Bucharest. The program combines economic and engineering knowledge and has students with both types of background. This multidisciplinary subject is well received by the students because they feel the transfer of skills needed on the 21st century labor market.