Value-Driven Data explains how data leaders and managers can develop data-driven opportunities and solutions for their organizations. By focusing on the value of data, Value-Driven Data explores how organizations can understand their business problems and come up with better solutions, aligning data storytelling with business needs. The book reviews the main challenges that plague most data-to-business interactions and offers actionable strategies for effective data value implementation, including methods for incentivising change. Value-Driven Data is supported by tried-and-tested frameworks that can be applied to different contexts and organizations. It features cutting-edge examples relating to digital transformation, data strategy, resolving conflicts of interests, building a data P&L and AI-driven value predictor methodology. The book recognizes different types of data value, ranging from data-based digital transformation to increased monetization, diversity and inclusion, and CSR goals. It explores conundrums such as data for commerce versus data for compassion and data profits versus data privacy. This will be essential reading for data specialists and leaders involved in capturing and executing data value opportunities for organizations and informing data-driven strategy.