To become a data-driven enterprise, companies must move from inflexible legacy data infrastructure that cannot scale to agile data architectures based on scaled-up, open-source systems that can handle any type or source of data. This involves storing both structured and unstructured high-volume, high-velocity data and then analyzing it through machine learning, predictive analytics, and real-time analytics to develop advanced analytical applications and globally scaled, data-driven applications. Achieving this requires expertise in agile development, DevOps, hybrid cloud, and continuous delivery to innovate with closed-loop applications.