The last few years have seen a tremendous paradigm shift in how institutional asset managers source and integrate multiple data sources into their investment process. With frequent shifts in risk correlations, unexpected sources of volatility, and increasing competition from passive strategies, asset managers are employing a broader set of third-party data sources to gain a competitive edge and improve risk-adjusted returns. However, the process of extracting benefits from multiple data sources can be extremely challenging. Asset managers’ data engineering teams are overloaded with data acquisition and preprocessing, while data science teams are mining data for investment insights.
Third-party or alternative data refers to data used in the investment process, sourced outside of the traditional market data providers. Institutional investors are frequently augmenting their traditional data sources with third-party or alternative data to gain an edge in their investment process. Typically cited examples include, but are not limited to, satellite imaging, credit

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