  Non-fungible tokens (NFT) have recently emerged as a novel blockchain hosted
financial asset class that has attracted major transaction volumes. Investment
decisions rely on data and adequate preprocessing and application of analytics
to them. Both owing to the non-fungible nature of the tokens and to a
blockchain being the primary data source, NFT transaction data pose several
challenges not commonly encountered in traditional financial data. Using data
that consist of the transaction history of eight highly valued NFT collections,
a selection of such challenges is illustrated. These are: price differentiation
by token traits, the possible existence of lateral swaps and wash trades in the
transaction history and finally, severe volatility. While this paper merely
scratches the surface of how data analytics can be applied in this context, the
data and challenges laid out here may present opportunities for future research
on the topic.
