De-identification is a common approach to working around or minimizing compliance risks related to personal data. In 2021, certain kinds of popular datasets, such as healthcare data, will likely require additional scrutiny as the coronavirus pandemic drags on and the accumulation of related datasets on the buyside increases the possibility of re-identification.

Trial licenses for data inspire mixed emotions in legal and compliance staff. The promise of free or inexpensive data (and less paperwork) appeals to both the front and back office; however, free data still presents risk with respect to diligence and contracting that may frustrate a buyer’s attempts to make special accommodations for trials.

We constantly hear concerns related to scraping. Many of these concerns are still expressed at a high level, indicating broad uncertainty even in the face of the hiQ Labs, Inc. v. LinkedIn Corporation decision.

The buyside is increasingly concerned with the quality of the alternative data that it collects. We have analyzed some of the data quality issues commonly raised by our buyside clients, whether they are looking to improve the performance of established data teams or considering building such a team. In this article we consider a few of the approaches already in play with (and potential approaches of) sophisticated buyers and sellers of alternative data.