How to Start Incorporating Machine Learning in the Enterprise Arena

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To understand more about the evolution of big data operations, I asked Justin Mullen about the challenges his company faced five years ago and why they were looking for modern integration platforms. He responded with, “We faced similar challenges to what our customers were facing. Before Big Data analytics, it was what I call

He responded with, “We faced similar challenges to what our customers were facing. Before Big Data analytics, it was what I call ‘Difficult Data analytics.’ There was a lot of manual aggregation and crunching of data from largely on-premise systems. And then the biggest challenge that we probably faced was centralizing and trusting the data before applying the different analytical algorithms available to analyze the raw data and visualize the results in meaningful ways for the business to understand.”

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