Smart livestock farming will enable real-time animal management to maximize health and efficiency. The dairy industry has been generating “big data” for many years for use in genetic and management decision making. Thus, a large existing data chain exists to implement smart farming, which is being augmented by new automated, high-throughput data collection tools (e.g., sensors, milking systems, images). Automated data collection and processing cyberinfrastructure will be central in facilitating real-time predictive analytics to provide actionable tasks for producers. Challenges in creating these systems include: network connectivity, sensor range, data dimensionality, data ownership/ privacy concerns, and development of effective predictive analytic cyberinfrastructure. Processing (i.e., cleaning, denoising, normalizing) should ideally allow rapid data mining, analytics and integration. Given the high value of data, preservation (i.e., backup) will be critical to prevent information loss. Capturing provenance (e.g., edits/ updates) and metadata will be important for downstream analytics. Livestock data has a broad array of uses from on-farm decision making to research, thus a broad range of animal and computational scientists should be involved in developing informatics systems. In principle, all data would be FAIR (Findable, Accessible, Interoperable, and Reusable) to encourage new research and expanded application. Protecting data ownership and maintaining privacy is an important consideration as downstream processing will likely require centralized cloud computing resources. Development of databases and software that facilitate machine learning, artificial intelligence or other prediction methods would help in improving computational efficiency and reduce wait time for analytic information. Thoughtful development of cyber-physical systems for smart farming could facilitate a new era of big data animal science. For producers, affordability, accuracy and sensitivity of analytic tools will determine if efforts to create automated data collection and processing systems will be fruitful.