Data structures are the foundation of software. Different components of a system may need the same information but may have different demands on its structure for reasons of performance, resource efficiency, technical constraints, convenience, and so on. For instance, transmitting data over a network requires a format that is suitable for serialization, while persisting data requires a format that is more suitable for storage. Thus, programmers need to translate data between several data structures and formats all the time. Authoring these translations manually is a lot of work because programmers need to implement the logic twice, once for each direction. This is redundant, tedious, and error-prone, and a case of low coherence. We show how using bidirectional data transformations that use functional optics like lenses and projections simplify the conversions. These ideas and techniques make converting data simple and straightforward and foster understanding of the relationship between data structures by explicitly describing their connections in a composable manner.