The Covid era is a proving ground. For example, alternative data providers have been espousing the wonders of their unique datasets, but if you can’t prove that your datasets are valuable in these volatile markets, the oxygen in the room is going to escape real quick.

Now stretching into its ninth month here in the US, the pandemic has also turned up the heat on machine-learning models that have historically relied on correlations between different types of datasets. Some very interesting work underway by IBM and Refinitiv could help brace these models for the future. Read More