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6 trends shaping the future of data analytics
Organizations are demanding more from their data analytics efforts, wanting immediate insights that will help drive business decisions. In response, many are adopting new technologies such as machine learning, deep learning and natural language processing. Eric Mizell, vice president of global solution engineering at Kinetica, discusses what role these technologies will plan in shaping the future of data analytics.
The algorithmic economy comes of age
“Organizations are dealing with a tsunami of data,” Mizell stresses. “The speed, size, shape of data generated by newer sources such as sensors, mobile apps, social media, machine logs, and connected devices far outpaces the ability of current systems and humans to comprehend, draw insights, and act on data. Organizations should look at algorithmic approaches such as machine learning, deep learning, and natural language processing (NLP) to automate insight discovery at scale.”