COVID-19 exposed long standing neglect in UK social care. This neglect cost lives. It underpinned failings in preparedness within the sector and failures in immediate responses by governments. Data, and the infrastructures that produce and mediate data, are implicated in both. At the start of the pandemic for instance, the UK government did not know who was in care homes, or even where those care homes were. Moral costs and consequences follow the absence from data of people, their interests and what they value. Interventions that bring benefits to certain people or groups may be unfairly distributed, and harms discounted. Problems also arose in how existing data came to categorise and value some individuals and groups while neglecting others. Furthermore, the pandemic amplified existing inequalities of epistemic power – the ability to use data was conferred at times to already well-represented groups while others were made ever less visible. These problems cannot be solved through the production of more data alone. Post-pandemic plans for digital transformation must attend to the effects of such enduring issues in addition to expanding data infrastructure. In this chapter I scrutinise some of these issues and their relationship to data through three theoretic-analytic lenses: complexities within social care systems; the human values which shape what the data measure and the decisions they inform; and the multiple scales at which data matter. I then use this framework to offer brief commentary on prospects of emerging policy promises in England.