September 2017: There’s No Machine Learning Without Learning

As the responsibilities of data professionals become more complex and wide-ranging, training will play an increasingly important role in ensuring efficiency, compliance and consistency.

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In this month’s issue, we cover topics ranging from the murky waters of commodity swaps data reporting to different uses of new machine-learning and artificial intelligence applications to automate processes, tag data, create personalized client experiences, calculate liquidity risk, and better inform trading strategies. In the past, sources say, learning the ropes of market and reference data was typically an on-the-job process—learning by osmosis, as some call it: immerse yourself in something

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