This chapter considers the emergence of data-driven analytics and its algorithmic techniques of imposing consequences as defining not just new modalities of governance but also as redefining governance forms, and consequently the ways that legalities entangle. The first step is to understand how data-driven governance differs from conventional forms of governance. One can then examine the points of entanglement and their character, whether within, between or beyond the conventional public law containers of legal space. At the centre is an examination of entanglement of law-norm systems and data-driven or social credit systems. That entanglement requires rationalizing a disjunction in how law/regulation systems understand data-driven metrics-based governance and vice versa, with the disjunction complicating entanglement. The first section briefly sketches the emerging legalities that neither embrace the form nor the language of law. The two sections that follow examine the nature of intersystemic entanglements when data-driven governance legal orders are thrown into the already plural mix. The first is the Chinese ‘social credit’ initiative. The second is US and Western private initiatives around emerging markets for data. Each exhibit distinct characteristics and therefore different forms and qualities of entanglement that suggest a more complex fracture and interacting among ever more different systems of legalities emerging around global trade regimes.