Given the potential predictive value of raw data, spending on big data continues to increase and is largely focused on third-party vendors. The goal is to leverage the data not only to generate alpha, but to respond to new regulatory requirements, reduce costs and assist with other operational and managerial functions. But how can fund managers successfully and economically achieve these aims? This article, the first in a three-part series, explores the big-data landscape and how fund managers can acquire and use big data. The second article
will analyze issues and best practices surrounding the acquisition of material nonpublic information; web-scraping; and the quality and testability of data. The third article
will discuss risks associated with data privacy, the acquisition of data from third parties and the use of drones, as well as ways fund managers can mitigate those risks. See “Tips and Warnings for Fund Managers When Navigating the Big Data Minefield
” (Sep. 13, 2017).